Spaces:
Running
on
Zero
Running
on
Zero
Rearrainge Blocks
Browse files- app.py +542 -430
- src/condition.py +1 -2
app.py
CHANGED
@@ -2,9 +2,12 @@ import os
|
|
2 |
# Import constants
|
3 |
import numpy as np
|
4 |
import torch
|
|
|
|
|
|
|
5 |
import utils.constants as constants
|
6 |
import gradio as gr
|
7 |
-
|
8 |
from haishoku.haishoku import Haishoku
|
9 |
|
10 |
from tempfile import NamedTemporaryFile
|
@@ -12,7 +15,7 @@ from tempfile import NamedTemporaryFile
|
|
12 |
import atexit
|
13 |
import random
|
14 |
import logging
|
15 |
-
import accelerate
|
16 |
from transformers import AutoTokenizer
|
17 |
import gc
|
18 |
|
@@ -26,8 +29,8 @@ from utils.color_utils import (
|
|
26 |
detect_color_format,
|
27 |
update_color_opacity,
|
28 |
)
|
29 |
-
from utils.misc import (get_filename, pause, convert_ratio_to_dimensions
|
30 |
-
from utils.depth_estimation import
|
31 |
|
32 |
from utils.image_utils import (
|
33 |
change_color,
|
@@ -40,7 +43,8 @@ from utils.image_utils import (
|
|
40 |
apply_lut_to_image_path,
|
41 |
multiply_and_blend_images,
|
42 |
alpha_composite_with_control,
|
43 |
-
crop_and_resize_image
|
|
|
44 |
)
|
45 |
|
46 |
from utils.hex_grid import (
|
@@ -64,7 +68,7 @@ from utils.version_info import (
|
|
64 |
versions_html,
|
65 |
#initialize_cuda,
|
66 |
#release_torch_resources,
|
67 |
-
get_torch_info
|
68 |
)
|
69 |
from utils.lora_details import (
|
70 |
upd_prompt_notes,
|
@@ -179,6 +183,117 @@ def get_model_and_lora(model_textbox):
|
|
179 |
default_model = model_textbox
|
180 |
return default_model, []
|
181 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
182 |
@spaces.GPU(progress=gr.Progress(track_tqdm=True))
|
183 |
def generate_image_lowmem(
|
184 |
text,
|
@@ -206,7 +321,7 @@ def generate_image_lowmem(
|
|
206 |
|
207 |
#initialize_cuda()
|
208 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
209 |
-
from src.condition import Condition
|
210 |
|
211 |
print(f"device:{device}\nmodel_name:{model_name}\nlora_weights:{lora_weights}\n")
|
212 |
#print(f"\n {get_torch_info()}\n")
|
@@ -481,7 +596,7 @@ def generate_ai_image_local (
|
|
481 |
gc.collect()
|
482 |
return None
|
483 |
|
484 |
-
@spaces.GPU(duration=140
|
485 |
def generate_input_image_click(map_option, prompt_textbox_value, negative_prompt_textbox_value, model_textbox_value, randomize_seed=True, seed=None, use_conditioned_image=False, strength=0.5, image_format="16:9", scale_factor=(8/3), progress=gr.Progress(track_tqdm=True)):
|
486 |
if randomize_seed:
|
487 |
seed = random.randint(0, constants.MAX_SEED)
|
@@ -566,465 +681,459 @@ def combine_images_with_lerp(input_image, output_image, alpha):
|
|
566 |
return lerp_imagemath(in_image, out_image, alpha)
|
567 |
|
568 |
def add_border(image, mask_width, mask_height, blank_color):
|
569 |
-
#install_torch()
|
570 |
bordered_image_output = Image.open(image).convert("RGBA")
|
571 |
margin_color = detect_color_format(blank_color)
|
572 |
print(f"Adding border to image with width: {mask_width}, height: {mask_height}, color: {margin_color}")
|
573 |
return shrink_and_paste_on_blank(bordered_image_output, mask_width, mask_height, margin_color)
|
574 |
|
575 |
-
@spaces.GPU()
|
576 |
def getVersions():
|
577 |
return versions_html()
|
|
|
578 |
generate_input_image_click.zerogpu = True
|
579 |
-
def main(debug=False):
|
580 |
-
|
581 |
-
|
582 |
-
|
583 |
|
584 |
-
|
585 |
|
586 |
-
|
587 |
-
|
588 |
-
|
589 |
-
|
590 |
-
|
591 |
-
|
592 |
-
|
593 |
-
|
594 |
-
|
595 |
|
596 |
-
|
597 |
|
598 |
|
599 |
|
600 |
-
|
601 |
-
|
602 |
-
|
603 |
-
|
604 |
-
|
605 |
-
|
606 |
-
|
607 |
-
|
608 |
-
|
609 |
-
|
610 |
-
|
611 |
-
|
612 |
-
|
613 |
-
|
614 |
-
|
615 |
-
|
616 |
-
|
617 |
-
|
618 |
-
|
619 |
-
|
620 |
-
|
621 |
-
|
622 |
-
|
623 |
-
|
624 |
-
|
625 |
-
|
626 |
-
|
627 |
-
|
628 |
-
|
629 |
-
|
630 |
-
|
631 |
-
|
632 |
|
633 |
-
|
634 |
-
|
635 |
-
|
636 |
-
|
637 |
-
|
638 |
-
|
639 |
-
|
640 |
-
|
641 |
-
|
642 |
-
|
643 |
-
|
644 |
-
|
645 |
-
|
646 |
-
|
647 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
648 |
)
|
649 |
|
650 |
-
|
651 |
-
|
652 |
-
|
653 |
-
|
654 |
-
|
655 |
-
|
656 |
-
|
657 |
-
|
658 |
-
|
659 |
-
|
660 |
-
|
661 |
-
|
662 |
-
|
663 |
-
|
664 |
-
|
665 |
-
|
666 |
-
|
667 |
-
|
668 |
-
with gr.Column():
|
669 |
-
filter_color = gr.Checkbox(label="Filter Excluded Colors from Sampling", value=False,)
|
670 |
-
exclude_color_button = gr.Button("Exclude Color", elem_id="exlude_color_button", elem_classes="solid")
|
671 |
-
color_display = gr.DataFrame(label="List of Excluded RGBA Colors", headers=["R", "G", "B", "A"], elem_id="excluded_colors", type="array", value=build_dataframe(excluded_color_list), interactive=True, elem_classes="solid centered")
|
672 |
-
selected_row = gr.Number(0, label="Selected Row", visible=False)
|
673 |
-
delete_button = gr.Button("Delete Row", elem_id="delete_exclusion_button", elem_classes="solid")
|
674 |
-
fill_hex = gr.Checkbox(label="Fill Hex with color from Image", value=True)
|
675 |
-
with gr.Accordion("Image Filters", open = False):
|
676 |
-
with gr.Row():
|
677 |
-
with gr.Column():
|
678 |
-
composite_color = gr.ColorPicker(label="Color", value="#ede9ac44")
|
679 |
-
with gr.Column():
|
680 |
-
composite_opacity = gr.Slider(label="Opacity %", minimum=0, maximum=100, value=50, interactive=True)
|
681 |
-
with gr.Row():
|
682 |
-
composite_button = gr.Button("Composite", elem_classes="solid")
|
683 |
with gr.Row():
|
684 |
with gr.Column():
|
685 |
-
|
686 |
-
|
687 |
-
|
688 |
-
|
689 |
-
|
690 |
-
|
691 |
-
|
692 |
-
file_count="single",
|
693 |
-
file_types=[".cube"],
|
694 |
-
type="filepath",
|
695 |
-
label="LUT cube File")
|
696 |
-
with gr.Row():
|
697 |
-
lut_example_image = gr.Image(type="pil", label="Filter (LUT) Example Image", value=constants.default_lut_example_img)
|
698 |
-
with gr.Row():
|
699 |
with gr.Column():
|
700 |
-
|
701 |
-
|
702 |
-
|
703 |
-
|
704 |
-
Try them on the example image before applying to your Input Image.
|
705 |
-
""", elem_id="lut_markdown")
|
706 |
with gr.Column():
|
707 |
-
gr.
|
708 |
-
|
709 |
-
|
710 |
-
|
711 |
-
|
|
|
|
|
712 |
)
|
713 |
-
|
714 |
-
|
715 |
-
|
716 |
-
|
717 |
-
|
718 |
-
|
719 |
-
|
720 |
-
lambda lut_filename, input_image: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image)[0],
|
721 |
-
inputs=[lut_filename, input_image],
|
722 |
-
outputs=[input_image],
|
723 |
-
scroll_to_output=True
|
724 |
)
|
725 |
-
|
726 |
-
|
727 |
-
|
728 |
-
|
729 |
-
|
730 |
-
|
731 |
-
|
732 |
-
|
733 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
734 |
elem_classes="solid"
|
735 |
-
|
736 |
-
|
737 |
-
|
738 |
-
|
739 |
-
elem_classes="solid",
|
740 |
-
elem_id="inference_model",
|
741 |
-
visible=False
|
742 |
-
)
|
743 |
-
# Update map_options to a Dropdown with choices from constants.PROMPTS keys
|
744 |
-
with gr.Row():
|
745 |
-
with gr.Column():
|
746 |
-
map_options = gr.Dropdown(
|
747 |
-
label="Map Options",
|
748 |
-
choices=list(constants.PROMPTS.keys()),
|
749 |
-
value="Alien Landscape",
|
750 |
-
elem_classes="solid",
|
751 |
-
scale=0
|
752 |
-
)
|
753 |
-
with gr.Column():
|
754 |
-
# Add Dropdown for sizing of Images, height and width based on selection. Options are 16x9, 16x10, 4x5, 1x1
|
755 |
-
# The values of height and width are based on common resolutions for each aspect ratio
|
756 |
-
# Default to 16x9, 912x512
|
757 |
-
image_size_ratio = gr.Dropdown(label="Image Size", choices=["16:9", "16:10", "4:5", "4:3", "2:1","3:2","1:1", "9:16", "10:16", "5:4", "3:4","1:2", "2:3"], value="16:9", elem_classes="solid", type="value", scale=0, interactive=True)
|
758 |
-
with gr.Column():
|
759 |
-
seed_slider = gr.Slider(
|
760 |
-
label="Seed",
|
761 |
-
minimum=0,
|
762 |
-
maximum=constants.MAX_SEED,
|
763 |
-
step=1,
|
764 |
-
value=0,
|
765 |
-
scale=0
|
766 |
-
)
|
767 |
-
randomize_seed = gr.Checkbox(label="Randomize seed", value=True, scale=0, interactive=True)
|
768 |
-
prompt_textbox = gr.Textbox(
|
769 |
-
label="Prompt",
|
770 |
-
visible=False,
|
771 |
-
elem_classes="solid",
|
772 |
-
value="top-down, (rectangular tabletop_map) alien planet map, Battletech_boardgame scifi world with forests, lakes, oceans, continents and snow at the top and bottom, (middle is dark, no_reflections, no_shadows), from directly above. From 100,000 feet looking straight down",
|
773 |
-
lines=4
|
774 |
-
)
|
775 |
-
negative_prompt_textbox = gr.Textbox(
|
776 |
-
label="Negative Prompt",
|
777 |
-
visible=False,
|
778 |
-
elem_classes="solid",
|
779 |
-
value="Earth, low quality, bad anatomy, blurry, cropped, worst quality, shadows, people, humans, reflections, shadows, realistic map of the Earth, isometric, text"
|
780 |
-
)
|
781 |
-
prompt_notes_label = gr.Label(
|
782 |
-
"You should use FRM$ as trigger words. @1.5 minutes",
|
783 |
-
elem_classes="solid centered small",
|
784 |
-
show_label=False,
|
785 |
-
visible=False
|
786 |
-
)
|
787 |
-
# Keep the change event to maintain functionality
|
788 |
-
map_options.change(
|
789 |
-
fn=update_prompt_visibility,
|
790 |
-
inputs=[map_options],
|
791 |
-
outputs=[prompt_textbox, negative_prompt_textbox, prompt_notes_label]
|
792 |
-
)
|
793 |
-
with gr.Row():
|
794 |
-
generate_input_image = gr.Button(
|
795 |
-
"Generate AI Image",
|
796 |
-
elem_id="generate_input_image",
|
797 |
-
elem_classes="solid"
|
798 |
-
)
|
799 |
-
with gr.Column(scale=2):
|
800 |
-
with gr.Accordion("Template Image Styles", open = False):
|
801 |
-
with gr.Row():
|
802 |
# Gallery from PRE_RENDERED_IMAGES GOES HERE
|
803 |
prerendered_image_gallery = gr.Gallery(label="Image Gallery", show_label=True, value=build_prerendered_images(constants.pre_rendered_maps_paths), elem_id="gallery", elem_classes="solid", type="filepath", columns=[3], rows=[3], preview=False ,object_fit="contain", height="auto", format="png",allow_preview=False)
|
804 |
-
|
805 |
-
|
806 |
-
|
807 |
-
|
808 |
-
|
809 |
-
|
810 |
-
|
811 |
-
|
812 |
-
|
813 |
-
|
814 |
-
|
815 |
-
|
816 |
-
|
817 |
-
|
818 |
-
|
819 |
-
|
820 |
-
with gr.Row():
|
821 |
-
start_x = gr.Number(label="Start X", value=0, minimum=-512, maximum= 512, precision=0)
|
822 |
-
start_y = gr.Number(label="Start Y", value=0, minimum=-512, maximum= 512, precision=0)
|
823 |
-
end_x = gr.Number(label="End X", value=0, minimum=-512, maximum= 512, precision=0)
|
824 |
-
end_y = gr.Number(label="End Y", value=0, minimum=-512, maximum= 512, precision=0)
|
825 |
-
with gr.Row():
|
826 |
-
x_spacing = gr.Number(label="Adjust Horizontal spacing", value=-1, minimum=-200, maximum=200, precision=1)
|
827 |
-
y_spacing = gr.Number(label="Adjust Vertical spacing", value=1, minimum=-200, maximum=200, precision=1)
|
828 |
-
with gr.Row():
|
829 |
-
rotation = gr.Slider(-90, 180, 0.0, 0.1, label="Hexagon Rotation (degree)")
|
830 |
-
add_hex_text = gr.Dropdown(label="Add Text to Hexagons", choices=[None, "Row-Column Coordinates", "Sequential Numbers", "Playing Cards Sequential", "Playing Cards Alternate Red and Black", "Custom List"], value=None)
|
831 |
-
with gr.Row():
|
832 |
-
custom_text_list = gr.TextArea(label="Custom Text List", value=constants.cards_alternating, visible=False,)
|
833 |
-
custom_text_color_list = gr.TextArea(label="Custom Text Color List", value=constants.card_colors_alternating, visible=False)
|
834 |
-
with gr.Row():
|
835 |
-
hex_text_info = gr.Markdown("""
|
836 |
-
### Text Color uses the Border Color and Border Opacity, unless you use a custom list.
|
837 |
-
### The Custom Text List and Custom Text Color List are comma separated lists.
|
838 |
-
### The custom color list is a comma separated list of hex colors.
|
839 |
-
#### Example: "A,2,3,4,5,6,7,8,9,10,J,Q,K", "red,#0000FF,#00FF00,red,#FFFF00,#00FFFF,#FF8000,#FF00FF,#FF0080,#FF8000,#FF0080,lightblue"
|
840 |
-
""", elem_id="hex_text_info", visible=False)
|
841 |
-
add_hex_text.change(
|
842 |
-
fn=lambda x: (
|
843 |
-
gr.update(visible=(x == "Custom List")),
|
844 |
-
gr.update(visible=(x == "Custom List")),
|
845 |
-
gr.update(visible=(x != None))
|
846 |
-
),
|
847 |
-
inputs=add_hex_text,
|
848 |
-
outputs=[custom_text_list, custom_text_color_list, hex_text_info]
|
849 |
-
)
|
850 |
with gr.Row():
|
851 |
-
|
852 |
-
|
853 |
-
|
854 |
-
|
855 |
-
background_opacity = gr.Slider(0,100,0,1,label="Background Opacity %")
|
856 |
-
border_color = gr.ColorPicker(label="Border Color", value="#7b7b7b", interactive=True)
|
857 |
-
border_opacity = gr.Slider(0,100,0,1,label="Border Opacity %")
|
858 |
with gr.Row():
|
859 |
-
|
|
|
860 |
with gr.Row():
|
861 |
-
|
862 |
-
|
863 |
with gr.Row():
|
864 |
-
|
865 |
-
|
866 |
-
|
867 |
-
|
868 |
-
|
869 |
-
|
870 |
-
|
871 |
-
|
872 |
-
|
873 |
-
|
874 |
-
|
875 |
-
|
876 |
-
|
877 |
-
|
878 |
-
|
879 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
880 |
|
881 |
-
|
882 |
-
with gr.Row():
|
883 |
-
with gr.Column():
|
884 |
-
voxel_size_factor = gr.Slider(label="Voxel Size Factor", value=1.00, minimum=0.01, maximum=40.00, step=0.01)
|
885 |
-
with gr.Column():
|
886 |
-
depth_image_source = gr.Radio(label="Depth Image Source", choices=["Input Image", "Output Image", "Overlay Image","Image with Margins"], value="Input Image")
|
887 |
-
with gr.Row():
|
888 |
-
generate_depth_button = gr.Button("Generate Depth Map and 3D Model From Selected Image", elem_classes="solid", variant="secondary")
|
889 |
-
with gr.Row():
|
890 |
-
depth_map_output = gr.Image(label="Depth Map", image_mode="L", elem_classes="centered solid imgcontainer", format="PNG", type="filepath", key="ImgDepth")
|
891 |
-
model_output = gr.Model3D(label="3D Model", clear_color=[1.0, 1.0, 1.0, 0.25], key="Img3D", elem_classes="centered solid imgcontainer")
|
892 |
with gr.Row():
|
893 |
-
gr.
|
894 |
-
|
895 |
-
|
896 |
-
|
897 |
-
["assets//examples//hexed_fract_1.png", False, True, 0,0,0,0,0,0,10,0,0,"#000000", 5],
|
898 |
-
["assets//examples//tmpzt3mblvk.png", False, True, -20,10,0,0,-6,-2,35,30,1,"#ffffff", 0],
|
899 |
-
],
|
900 |
-
inputs=[input_image, filter_color, fill_hex, start_x, start_y, end_x, end_y, x_spacing, y_spacing, hex_size, rotation, border_size, border_color, border_opacity],
|
901 |
-
elem_id="examples")
|
902 |
with gr.Row():
|
903 |
-
gr.
|
904 |
-
|
905 |
-
|
906 |
-
|
907 |
-
|
908 |
-
|
909 |
-
|
910 |
-
|
911 |
-
|
912 |
-
|
913 |
-
|
914 |
-
|
915 |
-
|
916 |
-
|
917 |
-
|
918 |
-
|
919 |
-
|
920 |
-
|
921 |
-
|
922 |
-
|
923 |
-
|
924 |
-
|
925 |
-
|
926 |
-
|
927 |
-
|
928 |
-
|
929 |
-
|
930 |
-
|
931 |
-
|
932 |
-
|
933 |
-
|
934 |
-
|
935 |
-
|
936 |
-
|
937 |
-
|
938 |
-
|
939 |
-
|
940 |
-
|
941 |
-
|
942 |
-
|
943 |
-
|
944 |
-
|
945 |
-
|
946 |
-
|
947 |
-
|
948 |
-
|
949 |
-
|
950 |
-
|
951 |
-
|
952 |
-
|
953 |
-
|
954 |
-
|
955 |
-
|
956 |
-
|
957 |
-
|
958 |
-
|
959 |
-
|
960 |
-
|
961 |
-
|
962 |
-
|
963 |
-
|
964 |
-
|
965 |
-
|
966 |
-
|
967 |
-
|
968 |
-
|
969 |
-
|
970 |
-
|
971 |
-
|
972 |
-
|
973 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
974 |
|
975 |
-
|
976 |
-
|
977 |
-
|
978 |
-
|
979 |
-
|
980 |
-
|
981 |
|
982 |
-
|
983 |
-
|
984 |
-
|
985 |
-
|
986 |
-
|
987 |
-
|
988 |
-
|
989 |
-
|
990 |
-
|
991 |
-
|
992 |
-
|
993 |
-
|
994 |
-
|
995 |
-
|
996 |
-
|
997 |
-
|
998 |
-
|
999 |
-
|
1000 |
-
|
1001 |
-
|
1002 |
-
|
1003 |
-
|
1004 |
-
|
1005 |
-
|
1006 |
-
|
1007 |
-
|
1008 |
-
|
1009 |
-
|
1010 |
-
|
1011 |
-
|
1012 |
-
|
1013 |
-
|
1014 |
-
|
1015 |
-
|
1016 |
-
|
1017 |
-
|
1018 |
|
1019 |
-
beeuty.queue(default_concurrency_limit=2,max_size=12,api_open=False)
|
1020 |
-
beeuty.launch(allowed_paths=["assets","/","./assets","images","./images", "./images/prerendered"], favicon_path="./assets/favicon.ico", max_file_size="10mb")
|
1021 |
|
1022 |
|
1023 |
-
if __name__ == "__main__":
|
1024 |
-
|
1025 |
-
|
1026 |
-
|
1027 |
-
|
1028 |
# if _get_output(["nvcc", "--version"]) is None:
|
1029 |
# logging.info("Installing CUDA toolkit...")
|
1030 |
# install_cuda_toolkit()
|
@@ -1034,4 +1143,7 @@ if __name__ == "__main__":
|
|
1034 |
# logging.info("Installing CUDA extensions...")
|
1035 |
# setup_runtime_env()
|
1036 |
#main(os.getenv("DEBUG") == "1")
|
1037 |
-
main()
|
|
|
|
|
|
|
|
2 |
# Import constants
|
3 |
import numpy as np
|
4 |
import torch
|
5 |
+
from typing import Optional, Union, List, Tuple
|
6 |
+
from PIL import Image, ImageFilter
|
7 |
+
import cv2
|
8 |
import utils.constants as constants
|
9 |
import gradio as gr
|
10 |
+
|
11 |
from haishoku.haishoku import Haishoku
|
12 |
|
13 |
from tempfile import NamedTemporaryFile
|
|
|
15 |
import atexit
|
16 |
import random
|
17 |
import logging
|
18 |
+
#import accelerate
|
19 |
from transformers import AutoTokenizer
|
20 |
import gc
|
21 |
|
|
|
29 |
detect_color_format,
|
30 |
update_color_opacity,
|
31 |
)
|
32 |
+
from utils.misc import (get_filename, pause, convert_ratio_to_dimensions) #install_cuda_toolkit,install_torch, _get_output, setup_runtime_env)
|
33 |
+
#from utils.depth_estimation import generate_depth_button_click
|
34 |
|
35 |
from utils.image_utils import (
|
36 |
change_color,
|
|
|
43 |
apply_lut_to_image_path,
|
44 |
multiply_and_blend_images,
|
45 |
alpha_composite_with_control,
|
46 |
+
crop_and_resize_image,
|
47 |
+
convert_to_rgba_png
|
48 |
)
|
49 |
|
50 |
from utils.hex_grid import (
|
|
|
68 |
versions_html,
|
69 |
#initialize_cuda,
|
70 |
#release_torch_resources,
|
71 |
+
#get_torch_info
|
72 |
)
|
73 |
from utils.lora_details import (
|
74 |
upd_prompt_notes,
|
|
|
183 |
default_model = model_textbox
|
184 |
return default_model, []
|
185 |
|
186 |
+
condition_dict = {
|
187 |
+
"depth": 0,
|
188 |
+
"canny": 1,
|
189 |
+
"subject": 4,
|
190 |
+
"coloring": 6,
|
191 |
+
"deblurring": 7,
|
192 |
+
"fill": 9,
|
193 |
+
}
|
194 |
+
|
195 |
+
class Condition(object):
|
196 |
+
def __init__(
|
197 |
+
self,
|
198 |
+
condition_type: str,
|
199 |
+
raw_img: Union[Image.Image, torch.Tensor] = None,
|
200 |
+
condition: Union[Image.Image,torch.Tensor] = None,
|
201 |
+
mask=None,
|
202 |
+
) -> None:
|
203 |
+
self.condition_type = condition_type
|
204 |
+
assert raw_img is not None or condition is not None
|
205 |
+
if raw_img is not None:
|
206 |
+
self.condition = self.get_condition(condition_type, raw_img)
|
207 |
+
else:
|
208 |
+
self.condition = condition
|
209 |
+
# TODO: Add mask support
|
210 |
+
assert mask is None, "Mask not supported yet"
|
211 |
+
def get_condition(
|
212 |
+
self, condition_type: str, raw_img: Union[Image.Image, torch.Tensor]
|
213 |
+
) -> Union[Image.Image, torch.Tensor]:
|
214 |
+
"""
|
215 |
+
Returns the condition image.
|
216 |
+
"""
|
217 |
+
if condition_type == "depth":
|
218 |
+
from transformers import pipeline
|
219 |
+
depth_pipe = pipeline(
|
220 |
+
task="depth-estimation",
|
221 |
+
model="LiheYoung/depth-anything-small-hf",
|
222 |
+
device="cuda",
|
223 |
+
)
|
224 |
+
source_image = raw_img.convert("RGB")
|
225 |
+
condition_img = depth_pipe(source_image)["depth"].convert("RGB")
|
226 |
+
return condition_img
|
227 |
+
elif condition_type == "canny":
|
228 |
+
img = np.array(raw_img)
|
229 |
+
edges = cv2.Canny(img, 100, 200)
|
230 |
+
edges = Image.fromarray(edges).convert("RGB")
|
231 |
+
return edges
|
232 |
+
elif condition_type == "subject":
|
233 |
+
return raw_img
|
234 |
+
elif condition_type == "coloring":
|
235 |
+
return raw_img.convert("L").convert("RGB")
|
236 |
+
elif condition_type == "deblurring":
|
237 |
+
condition_image = (
|
238 |
+
raw_img.convert("RGB")
|
239 |
+
.filter(ImageFilter.GaussianBlur(10))
|
240 |
+
.convert("RGB")
|
241 |
+
)
|
242 |
+
return condition_image
|
243 |
+
elif condition_type == "fill":
|
244 |
+
return raw_img.convert("RGB")
|
245 |
+
return self.condition
|
246 |
+
@property
|
247 |
+
def type_id(self) -> int:
|
248 |
+
"""
|
249 |
+
Returns the type id of the condition.
|
250 |
+
"""
|
251 |
+
return condition_dict[self.condition_type]
|
252 |
+
@classmethod
|
253 |
+
def get_type_id(cls, condition_type: str) -> int:
|
254 |
+
"""
|
255 |
+
Returns the type id of the condition.
|
256 |
+
"""
|
257 |
+
return condition_dict[condition_type]
|
258 |
+
def _encode_image(self, pipe: FluxPipeline, cond_img: Image.Image) -> torch.Tensor:
|
259 |
+
"""
|
260 |
+
Encodes an image condition into tokens using the pipeline.
|
261 |
+
"""
|
262 |
+
cond_img = pipe.image_processor.preprocess(cond_img)
|
263 |
+
cond_img = cond_img.to(pipe.device).to(pipe.dtype)
|
264 |
+
cond_img = pipe.vae.encode(cond_img).latent_dist.sample()
|
265 |
+
cond_img = (
|
266 |
+
cond_img - pipe.vae.config.shift_factor
|
267 |
+
) * pipe.vae.config.scaling_factor
|
268 |
+
cond_tokens = pipe._pack_latents(cond_img, *cond_img.shape)
|
269 |
+
cond_ids = pipe._prepare_latent_image_ids(
|
270 |
+
cond_img.shape[0],
|
271 |
+
cond_img.shape[2]//2,
|
272 |
+
cond_img.shape[3]//2,
|
273 |
+
pipe.device,
|
274 |
+
pipe.dtype,
|
275 |
+
)
|
276 |
+
return cond_tokens, cond_ids
|
277 |
+
def encode(self, pipe: FluxPipeline) -> Tuple[torch.Tensor, torch.Tensor, int]:
|
278 |
+
"""
|
279 |
+
Encodes the condition into tokens, ids and type_id.
|
280 |
+
"""
|
281 |
+
if self.condition_type in [
|
282 |
+
"depth",
|
283 |
+
"canny",
|
284 |
+
"subject",
|
285 |
+
"coloring",
|
286 |
+
"deblurring",
|
287 |
+
"fill",
|
288 |
+
]:
|
289 |
+
tokens, ids = self._encode_image(pipe, self.condition)
|
290 |
+
else:
|
291 |
+
raise NotImplementedError(
|
292 |
+
f"Condition type {self.condition_type} not implemented"
|
293 |
+
)
|
294 |
+
type_id = torch.ones_like(ids[:, :1]) * self.type_id
|
295 |
+
return tokens, ids, type_id
|
296 |
+
|
297 |
@spaces.GPU(progress=gr.Progress(track_tqdm=True))
|
298 |
def generate_image_lowmem(
|
299 |
text,
|
|
|
321 |
|
322 |
#initialize_cuda()
|
323 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
324 |
+
#from src.condition import Condition
|
325 |
|
326 |
print(f"device:{device}\nmodel_name:{model_name}\nlora_weights:{lora_weights}\n")
|
327 |
#print(f"\n {get_torch_info()}\n")
|
|
|
596 |
gc.collect()
|
597 |
return None
|
598 |
|
599 |
+
@spaces.GPU(duration=140)
|
600 |
def generate_input_image_click(map_option, prompt_textbox_value, negative_prompt_textbox_value, model_textbox_value, randomize_seed=True, seed=None, use_conditioned_image=False, strength=0.5, image_format="16:9", scale_factor=(8/3), progress=gr.Progress(track_tqdm=True)):
|
601 |
if randomize_seed:
|
602 |
seed = random.randint(0, constants.MAX_SEED)
|
|
|
681 |
return lerp_imagemath(in_image, out_image, alpha)
|
682 |
|
683 |
def add_border(image, mask_width, mask_height, blank_color):
|
|
|
684 |
bordered_image_output = Image.open(image).convert("RGBA")
|
685 |
margin_color = detect_color_format(blank_color)
|
686 |
print(f"Adding border to image with width: {mask_width}, height: {mask_height}, color: {margin_color}")
|
687 |
return shrink_and_paste_on_blank(bordered_image_output, mask_width, mask_height, margin_color)
|
688 |
|
|
|
689 |
def getVersions():
|
690 |
return versions_html()
|
691 |
+
|
692 |
generate_input_image_click.zerogpu = True
|
693 |
+
#def main(debug=False):
|
694 |
+
title = "HexaGrid Creator"
|
695 |
+
#description = "Customizable Hexagon Grid Image Generator"
|
696 |
+
examples = [["assets//examples//hex_map_p1.png", 32, 1, 0, 0, 0, 0, 0, "#ede9ac44","#12165380", True]]
|
697 |
|
698 |
+
gr.set_static_paths(paths=["images/","images/images","images/prerendered","LUT/","fonts/"])
|
699 |
|
700 |
+
# Gradio Blocks Interface
|
701 |
+
with gr.Blocks(css_paths="style_20250128.css", title=title, theme='Surn/beeuty') as hexaGrid:
|
702 |
+
with gr.Row():
|
703 |
+
gr.Markdown("""
|
704 |
+
# HexaGrid Creator
|
705 |
+
## Transform Your Images into Mesmerizing Hexagon Grid Masterpieces! ⬢""", elem_classes="intro")
|
706 |
+
with gr.Row():
|
707 |
+
with gr.Accordion("Welcome to HexaGrid Creator, the ultimate tool for transforming your images into stunning hexagon grid artworks. Whether you're a tabletop game enthusiast, a digital artist, or someone who loves unique patterns, HexaGrid Creator has something for you.", open=False, elem_classes="intro"):
|
708 |
+
gr.Markdown ("""
|
709 |
|
710 |
+
## Drop an image into the Input Image and get started!
|
711 |
|
712 |
|
713 |
|
714 |
+
## What is HexaGrid Creator?
|
715 |
+
HexaGrid Creator is a web-based application that allows you to apply a hexagon grid overlay to any image. You can customize the size, color, and opacity of the hexagons, as well as the background and border colors. The result is a visually striking image that looks like it was made from hexagonal tiles!
|
716 |
+
|
717 |
+
### What Can You Do?
|
718 |
+
- **Generate Hexagon Grids:** Create beautiful hexagon grid overlays on any image with fully customizable parameters.
|
719 |
+
- **AI-Powered Image Generation:** Use advanced AI models to generate images based on your prompts and apply hexagon grids to them.
|
720 |
+
- **Color Exclusion:** Select and exclude specific colors from your hexagon grid for a cleaner and more refined look.
|
721 |
+
- **Interactive Customization:** Adjust hexagon size, border size, rotation, background color, and more in real-time.
|
722 |
+
- **Depth and 3D Model Generation:** Generate depth maps and 3D models from your images for enhanced visualization.
|
723 |
+
- **Image Filter [Look-Up Table (LUT)] Application:** Apply filters (LUTs) to your images for color grading and enhancement.
|
724 |
+
- **Pre-rendered Maps:** Access a library of pre-rendered hexagon maps for quick and easy customization.
|
725 |
+
- **Add Margins:** Add customizable margins around your images for a polished finish.
|
726 |
+
|
727 |
+
### Why You'll Love It
|
728 |
+
- **Fun and Easy to Use:** With an intuitive interface and real-time previews, creating hexagon grids has never been this fun!
|
729 |
+
- **Endless Creativity:** Unleash your creativity with endless customization options and see your images transform in unique ways.
|
730 |
+
- **Hexagon-Inspired Theme:** Enjoy a delightful yellow and purple theme inspired by hexagons! ⬢
|
731 |
+
- **Advanced AI Models:** Leverage advanced AI models and LoRA weights for high-quality image generation and customization.
|
732 |
+
|
733 |
+
### Get Started
|
734 |
+
1. **Upload or Generate an Image:** Start by uploading your own image or generate one using our AI-powered tool.
|
735 |
+
2. **Customize Your Grid:** Play around with the settings to create the perfect hexagon grid overlay.
|
736 |
+
3. **Download and Share:** Once you're happy with your creation, download it and share it with the world!
|
737 |
+
|
738 |
+
### Advanced Features
|
739 |
+
- **Generative AI Integration:** Utilize models like `black-forest-labs/FLUX.1-dev` and various LoRA weights for generating unique images.
|
740 |
+
- **Pre-rendered Maps:** Access a library of pre-rendered hexagon maps for quick and easy customization.
|
741 |
+
- **Image Filter [Look-Up Table (LUT)] Application:** Apply filters (LUTs) to your images for color grading and enhancement.
|
742 |
+
- **Depth and 3D Model Generation:** Create depth maps and 3D models from your images for enhanced visualization.
|
743 |
+
- **Add Margins:** Customize margins around your images for a polished finish.
|
744 |
+
|
745 |
+
Join the hive and start creating with HexaGrid Creator today!
|
746 |
|
747 |
+
""", elem_classes="intro")
|
748 |
+
with gr.Row():
|
749 |
+
with gr.Column(scale=2):
|
750 |
+
input_image = gr.Image(
|
751 |
+
label="Input Image",
|
752 |
+
type="filepath",
|
753 |
+
interactive=True,
|
754 |
+
elem_classes="centered solid imgcontainer",
|
755 |
+
key="imgInput",
|
756 |
+
image_mode=None,
|
757 |
+
format="PNG",
|
758 |
+
show_download_button=True,
|
759 |
+
)
|
760 |
+
|
761 |
+
# New code to convert input image to RGBA PNG
|
762 |
+
def on_input_image_change(image_path):
|
763 |
+
if image_path is None:
|
764 |
+
gr.Warning("Please upload an Input Image to get started.")
|
765 |
+
return None
|
766 |
+
img, img_path = convert_to_rgba_png(image_path)
|
767 |
+
return img_path
|
768 |
+
|
769 |
+
input_image.change(
|
770 |
+
fn=on_input_image_change,
|
771 |
+
inputs=[input_image],
|
772 |
+
outputs=[input_image], scroll_to_output=True,
|
773 |
+
)
|
774 |
+
with gr.Column():
|
775 |
+
with gr.Accordion("Hex Coloring and Exclusion", open = False):
|
776 |
+
with gr.Row():
|
777 |
+
with gr.Column():
|
778 |
+
color_picker = gr.ColorPicker(label="Pick a color to exclude",value="#505050")
|
779 |
+
with gr.Column():
|
780 |
+
filter_color = gr.Checkbox(label="Filter Excluded Colors from Sampling", value=False,)
|
781 |
+
exclude_color_button = gr.Button("Exclude Color", elem_id="exlude_color_button", elem_classes="solid")
|
782 |
+
color_display = gr.DataFrame(label="List of Excluded RGBA Colors", headers=["R", "G", "B", "A"], elem_id="excluded_colors", type="array", value=build_dataframe(excluded_color_list), interactive=True, elem_classes="solid centered")
|
783 |
+
selected_row = gr.Number(0, label="Selected Row", visible=False)
|
784 |
+
delete_button = gr.Button("Delete Row", elem_id="delete_exclusion_button", elem_classes="solid")
|
785 |
+
fill_hex = gr.Checkbox(label="Fill Hex with color from Image", value=True)
|
786 |
+
with gr.Accordion("Image Filters", open = False):
|
787 |
+
with gr.Row():
|
788 |
+
with gr.Column():
|
789 |
+
composite_color = gr.ColorPicker(label="Color", value="#ede9ac44")
|
790 |
+
with gr.Column():
|
791 |
+
composite_opacity = gr.Slider(label="Opacity %", minimum=0, maximum=100, value=50, interactive=True)
|
792 |
+
with gr.Row():
|
793 |
+
composite_button = gr.Button("Composite", elem_classes="solid")
|
794 |
+
with gr.Row():
|
795 |
+
with gr.Column():
|
796 |
+
lut_filename = gr.Textbox(
|
797 |
+
value="",
|
798 |
+
label="Look Up Table (LUT) File Name",
|
799 |
+
elem_id="lutFileName")
|
800 |
+
with gr.Column():
|
801 |
+
lut_file = gr.File(
|
802 |
+
value=None,
|
803 |
+
file_count="single",
|
804 |
+
file_types=[".cube"],
|
805 |
+
type="filepath",
|
806 |
+
label="LUT cube File")
|
807 |
+
with gr.Row():
|
808 |
+
lut_example_image = gr.Image(type="pil", label="Filter (LUT) Example Image", value=constants.default_lut_example_img)
|
809 |
+
with gr.Row():
|
810 |
+
with gr.Column():
|
811 |
+
gr.Markdown("""
|
812 |
+
### Included Filters (LUTs)
|
813 |
+
There are several included Filters:
|
814 |
+
|
815 |
+
Try them on the example image before applying to your Input Image.
|
816 |
+
""", elem_id="lut_markdown")
|
817 |
+
with gr.Column():
|
818 |
+
gr.Examples(elem_id="lut_examples",
|
819 |
+
examples=[[f] for f in constants.lut_files],
|
820 |
+
inputs=[lut_filename],
|
821 |
+
outputs=[lut_filename],
|
822 |
+
label="Select a Filter (LUT) file. Populate the LUT File Name field"
|
823 |
+
)
|
824 |
+
|
825 |
+
with gr.Row():
|
826 |
+
apply_lut_button = gr.Button("Apply Filter (LUT)", elem_classes="solid", elem_id="apply_lut_button")
|
827 |
+
|
828 |
+
lut_file.change(get_filename, inputs=[lut_file], outputs=[lut_filename])
|
829 |
+
lut_filename.change(show_lut, inputs=[lut_filename, lut_example_image], outputs=[lut_example_image])
|
830 |
+
apply_lut_button.click(
|
831 |
+
lambda lut_filename, input_image: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image)[0],
|
832 |
+
inputs=[lut_filename, input_image],
|
833 |
+
outputs=[input_image],
|
834 |
+
scroll_to_output=True
|
835 |
)
|
836 |
|
837 |
+
with gr.Row():
|
838 |
+
with gr.Accordion("Generative AI", open = False):
|
839 |
+
with gr.Row():
|
840 |
+
with gr.Column():
|
841 |
+
model_options = gr.Dropdown(
|
842 |
+
label="Model Options",
|
843 |
+
choices=constants.MODELS + constants.LORA_WEIGHTS + ["Manual Entry"],
|
844 |
+
value="Cossale/Frames2-Flex.1",
|
845 |
+
elem_classes="solid"
|
846 |
+
)
|
847 |
+
model_textbox = gr.Textbox(
|
848 |
+
label="LORA/Model",
|
849 |
+
value="Cossale/Frames2-Flex.1",
|
850 |
+
elem_classes="solid",
|
851 |
+
elem_id="inference_model",
|
852 |
+
visible=False
|
853 |
+
)
|
854 |
+
# Update map_options to a Dropdown with choices from constants.PROMPTS keys
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
855 |
with gr.Row():
|
856 |
with gr.Column():
|
857 |
+
map_options = gr.Dropdown(
|
858 |
+
label="Map Options",
|
859 |
+
choices=list(constants.PROMPTS.keys()),
|
860 |
+
value="Alien Landscape",
|
861 |
+
elem_classes="solid",
|
862 |
+
scale=0
|
863 |
+
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
864 |
with gr.Column():
|
865 |
+
# Add Dropdown for sizing of Images, height and width based on selection. Options are 16x9, 16x10, 4x5, 1x1
|
866 |
+
# The values of height and width are based on common resolutions for each aspect ratio
|
867 |
+
# Default to 16x9, 912x512
|
868 |
+
image_size_ratio = gr.Dropdown(label="Image Size", choices=["16:9", "16:10", "4:5", "4:3", "2:1","3:2","1:1", "9:16", "10:16", "5:4", "3:4","1:2", "2:3"], value="16:9", elem_classes="solid", type="value", scale=0, interactive=True)
|
|
|
|
|
869 |
with gr.Column():
|
870 |
+
seed_slider = gr.Slider(
|
871 |
+
label="Seed",
|
872 |
+
minimum=0,
|
873 |
+
maximum=constants.MAX_SEED,
|
874 |
+
step=1,
|
875 |
+
value=0,
|
876 |
+
scale=0
|
877 |
)
|
878 |
+
randomize_seed = gr.Checkbox(label="Randomize seed", value=True, scale=0, interactive=True)
|
879 |
+
prompt_textbox = gr.Textbox(
|
880 |
+
label="Prompt",
|
881 |
+
visible=False,
|
882 |
+
elem_classes="solid",
|
883 |
+
value="top-down, (rectangular tabletop_map) alien planet map, Battletech_boardgame scifi world with forests, lakes, oceans, continents and snow at the top and bottom, (middle is dark, no_reflections, no_shadows), from directly above. From 100,000 feet looking straight down",
|
884 |
+
lines=4
|
|
|
|
|
|
|
|
|
885 |
)
|
886 |
+
negative_prompt_textbox = gr.Textbox(
|
887 |
+
label="Negative Prompt",
|
888 |
+
visible=False,
|
889 |
+
elem_classes="solid",
|
890 |
+
value="Earth, low quality, bad anatomy, blurry, cropped, worst quality, shadows, people, humans, reflections, shadows, realistic map of the Earth, isometric, text"
|
891 |
+
)
|
892 |
+
prompt_notes_label = gr.Label(
|
893 |
+
"You should use FRM$ as trigger words. @1.5 minutes",
|
894 |
+
elem_classes="solid centered small",
|
895 |
+
show_label=False,
|
896 |
+
visible=False
|
897 |
+
)
|
898 |
+
# Keep the change event to maintain functionality
|
899 |
+
map_options.change(
|
900 |
+
fn=update_prompt_visibility,
|
901 |
+
inputs=[map_options],
|
902 |
+
outputs=[prompt_textbox, negative_prompt_textbox, prompt_notes_label]
|
903 |
+
)
|
904 |
+
with gr.Row():
|
905 |
+
generate_input_image = gr.Button(
|
906 |
+
"Generate AI Image",
|
907 |
+
elem_id="generate_input_image",
|
908 |
elem_classes="solid"
|
909 |
+
)
|
910 |
+
with gr.Column(scale=2):
|
911 |
+
with gr.Accordion("Template Image Styles", open = False):
|
912 |
+
with gr.Row():
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
913 |
# Gallery from PRE_RENDERED_IMAGES GOES HERE
|
914 |
prerendered_image_gallery = gr.Gallery(label="Image Gallery", show_label=True, value=build_prerendered_images(constants.pre_rendered_maps_paths), elem_id="gallery", elem_classes="solid", type="filepath", columns=[3], rows=[3], preview=False ,object_fit="contain", height="auto", format="png",allow_preview=False)
|
915 |
+
with gr.Row():
|
916 |
+
image_guidance_stength = gr.Slider(label="Image Guidance Strength (prompt percentage)", minimum=0, maximum=1.0, value=0.8, step=0.01, interactive=True)
|
917 |
+
with gr.Column():
|
918 |
+
replace_input_image_button = gr.Button(
|
919 |
+
"Replace Input Image",
|
920 |
+
elem_id="prerendered_replace_input_image_button",
|
921 |
+
elem_classes="solid"
|
922 |
+
)
|
923 |
+
with gr.Column():
|
924 |
+
generate_input_image_from_gallery = gr.Button(
|
925 |
+
"Generate AI Image from Gallery",
|
926 |
+
elem_id="generate_input_image_from_gallery",
|
927 |
+
elem_classes="solid"
|
928 |
+
)
|
929 |
+
|
930 |
+
with gr.Accordion("Advanced Hexagon Settings", open = False):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
931 |
with gr.Row():
|
932 |
+
start_x = gr.Number(label="Start X", value=0, minimum=-512, maximum= 512, precision=0)
|
933 |
+
start_y = gr.Number(label="Start Y", value=0, minimum=-512, maximum= 512, precision=0)
|
934 |
+
end_x = gr.Number(label="End X", value=0, minimum=-512, maximum= 512, precision=0)
|
935 |
+
end_y = gr.Number(label="End Y", value=0, minimum=-512, maximum= 512, precision=0)
|
|
|
|
|
|
|
936 |
with gr.Row():
|
937 |
+
x_spacing = gr.Number(label="Adjust Horizontal spacing", value=-1, minimum=-200, maximum=200, precision=1)
|
938 |
+
y_spacing = gr.Number(label="Adjust Vertical spacing", value=1, minimum=-200, maximum=200, precision=1)
|
939 |
with gr.Row():
|
940 |
+
rotation = gr.Slider(-90, 180, 0.0, 0.1, label="Hexagon Rotation (degree)")
|
941 |
+
add_hex_text = gr.Dropdown(label="Add Text to Hexagons", choices=[None, "Row-Column Coordinates", "Sequential Numbers", "Playing Cards Sequential", "Playing Cards Alternate Red and Black", "Custom List"], value=None)
|
942 |
with gr.Row():
|
943 |
+
custom_text_list = gr.TextArea(label="Custom Text List", value=constants.cards_alternating, visible=False,)
|
944 |
+
custom_text_color_list = gr.TextArea(label="Custom Text Color List", value=constants.card_colors_alternating, visible=False)
|
945 |
+
with gr.Row():
|
946 |
+
hex_text_info = gr.Markdown("""
|
947 |
+
### Text Color uses the Border Color and Border Opacity, unless you use a custom list.
|
948 |
+
### The Custom Text List and Custom Text Color List are comma separated lists.
|
949 |
+
### The custom color list is a comma separated list of hex colors.
|
950 |
+
#### Example: "A,2,3,4,5,6,7,8,9,10,J,Q,K", "red,#0000FF,#00FF00,red,#FFFF00,#00FFFF,#FF8000,#FF00FF,#FF0080,#FF8000,#FF0080,lightblue"
|
951 |
+
""", elem_id="hex_text_info", visible=False)
|
952 |
+
add_hex_text.change(
|
953 |
+
fn=lambda x: (
|
954 |
+
gr.update(visible=(x == "Custom List")),
|
955 |
+
gr.update(visible=(x == "Custom List")),
|
956 |
+
gr.update(visible=(x != None))
|
957 |
+
),
|
958 |
+
inputs=add_hex_text,
|
959 |
+
outputs=[custom_text_list, custom_text_color_list, hex_text_info]
|
960 |
+
)
|
961 |
+
with gr.Row():
|
962 |
+
hex_size = gr.Number(label="Hexagon Size", value=32, minimum=1, maximum=768)
|
963 |
+
border_size = gr.Slider(-5,25,value=0,step=1,label="Border Size")
|
964 |
+
with gr.Row():
|
965 |
+
background_color = gr.ColorPicker(label="Background Color", value="#000000", interactive=True)
|
966 |
+
background_opacity = gr.Slider(0,100,0,1,label="Background Opacity %")
|
967 |
+
border_color = gr.ColorPicker(label="Border Color", value="#7b7b7b", interactive=True)
|
968 |
+
border_opacity = gr.Slider(0,100,0,1,label="Border Opacity %")
|
969 |
+
with gr.Row():
|
970 |
+
hex_button = gr.Button("Generate Hex Grid!", elem_classes="solid", elem_id="btn-generate")
|
971 |
+
with gr.Row():
|
972 |
+
output_image = gr.Image(label="Hexagon Grid Image", image_mode = "RGBA", show_download_button=True, show_share_button=True,elem_classes="centered solid imgcontainer", format="PNG", type="filepath", key="ImgOutput")
|
973 |
+
overlay_image = gr.Image(label="Hexagon Overlay Image", image_mode = "RGBA", show_share_button=True, elem_classes="centered solid imgcontainer", format="PNG", type="filepath", key="ImgOverlay")
|
974 |
+
with gr.Row():
|
975 |
+
output_overlay_composite = gr.Slider(0,100,50,0.5, label="Interpolate Intensity")
|
976 |
+
output_blend_multiply_composite = gr.Slider(0,100,50,0.5, label="Overlay Intensity")
|
977 |
+
output_alpha_composite = gr.Slider(0,100,50,0.5, label="Alpha Composite Intensity")
|
978 |
+
with gr.Accordion("Add Margins (bleed)", open=False):
|
979 |
+
with gr.Row():
|
980 |
+
border_image_source = gr.Radio(label="Add Margins around which Image", choices=["Input Image", "Overlay Image"], value="Overlay Image")
|
981 |
+
with gr.Row():
|
982 |
+
mask_width = gr.Number(label="Margins Width", value=10, minimum=0, maximum=100, precision=0)
|
983 |
+
mask_height = gr.Number(label="Margins Height", value=10, minimum=0, maximum=100, precision=0)
|
984 |
+
with gr.Row():
|
985 |
+
margin_color = gr.ColorPicker(label="Margin Color", value="#333333FF", interactive=True)
|
986 |
+
margin_opacity = gr.Slider(0,100,95,0.5,label="Margin Opacity %")
|
987 |
+
with gr.Row():
|
988 |
+
add_border_button = gr.Button("Add Margins", elem_classes="solid", variant="secondary")
|
989 |
+
with gr.Row():
|
990 |
+
bordered_image_output = gr.Image(label="Image with Margins", image_mode="RGBA", show_download_button=True, show_share_button=True, elem_classes="centered solid imgcontainer", format="PNG", type="filepath", key="ImgBordered")
|
991 |
|
992 |
+
with gr.Accordion("Height Maps and 3D", open = False):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
993 |
with gr.Row():
|
994 |
+
with gr.Column():
|
995 |
+
voxel_size_factor = gr.Slider(label="Voxel Size Factor", value=1.00, minimum=0.01, maximum=40.00, step=0.01)
|
996 |
+
with gr.Column():
|
997 |
+
depth_image_source = gr.Radio(label="Depth Image Source", choices=["Input Image", "Output Image", "Overlay Image","Image with Margins"], value="Input Image")
|
|
|
|
|
|
|
|
|
|
|
998 |
with gr.Row():
|
999 |
+
generate_depth_button = gr.Button("Generate Depth Map and 3D Model From Selected Image", elem_classes="solid", variant="secondary")
|
1000 |
+
with gr.Row():
|
1001 |
+
depth_map_output = gr.Image(label="Depth Map", image_mode="L", elem_classes="centered solid imgcontainer", format="PNG", type="filepath", key="ImgDepth")
|
1002 |
+
model_output = gr.Model3D(label="3D Model", clear_color=[1.0, 1.0, 1.0, 0.25], key="Img3D", elem_classes="centered solid imgcontainer")
|
1003 |
+
with gr.Row():
|
1004 |
+
gr.Examples(examples=[
|
1005 |
+
["assets//examples//hex_map_p1.png", False, True, -32,-31,80,80,-1.8,0,35,0,1,"#FFD0D0", 15],
|
1006 |
+
["assets//examples//hex_map_p1_overlayed.png", False, False, -32,-31,80,80,-1.8,0,35,0,1,"#FFD0D0", 75],
|
1007 |
+
["assets//examples//hex_flower_logo.png", False, True, -95,-95,100,100,-24,-2,190,30,2,"#FF8951", 50],
|
1008 |
+
["assets//examples//hexed_fract_1.png", False, True, 0,0,0,0,0,0,10,0,0,"#000000", 5],
|
1009 |
+
["assets//examples//tmpzt3mblvk.png", False, True, -20,10,0,0,-6,-2,35,30,1,"#ffffff", 0],
|
1010 |
+
],
|
1011 |
+
inputs=[input_image, filter_color, fill_hex, start_x, start_y, end_x, end_y, x_spacing, y_spacing, hex_size, rotation, border_size, border_color, border_opacity],
|
1012 |
+
elem_id="examples")
|
1013 |
+
with gr.Row():
|
1014 |
+
gr.HTML(value=getVersions(), visible=True, elem_id="versions")
|
1015 |
+
# with gr.Row():
|
1016 |
+
# reinstall_torch = gr.Button("Reinstall Torch", elem_classes="solid small", variant="secondary")
|
1017 |
+
# reinstall_cuda_toolkit = gr.Button("Install CUDA Toolkit", elem_classes="solid small", variant="secondary")
|
1018 |
+
# reinitialize_cuda = gr.Button("Reinitialize CUDA", elem_classes="solid small", variant="secondary")
|
1019 |
+
# torch_release = gr.Button("Release Torch Resources", elem_classes="solid small", variant="secondary")
|
1020 |
+
|
1021 |
+
# reinitialize_cuda.click(
|
1022 |
+
# fn=initialize_cuda,
|
1023 |
+
# inputs=[],
|
1024 |
+
# outputs=[]
|
1025 |
+
# )
|
1026 |
+
# torch_release.click(
|
1027 |
+
# fn=release_torch_resources,
|
1028 |
+
# inputs=[],
|
1029 |
+
# outputs=[]
|
1030 |
+
# )
|
1031 |
+
# reinstall_torch.click(
|
1032 |
+
# fn=install_torch,
|
1033 |
+
# inputs=[],
|
1034 |
+
# outputs=[]
|
1035 |
+
# )
|
1036 |
+
|
1037 |
+
# reinstall_cuda_toolkit.click(
|
1038 |
+
# fn=install_cuda_toolkit,
|
1039 |
+
# inputs=[],
|
1040 |
+
# outputs=[]
|
1041 |
+
# )
|
1042 |
+
|
1043 |
+
color_display.select(on_color_display_select,inputs=[color_display], outputs=[selected_row])
|
1044 |
+
color_display.input(on_input,inputs=[color_display], outputs=[color_display, gr.State(excluded_color_list)])
|
1045 |
+
|
1046 |
+
delete_button.click(fn=delete_color, inputs=[selected_row, color_display], outputs=[color_display])
|
1047 |
+
exclude_color_button.click(fn=add_color, inputs=[color_picker, gr.State(excluded_color_list)], outputs=[color_display, gr.State(excluded_color_list)])
|
1048 |
+
hex_button.click(
|
1049 |
+
fn=lambda hex_size, border_size, input_image, start_x, start_y, end_x, end_y, rotation, background_color, background_opacity, border_color, border_opacity, fill_hex, color_display, filter_color, x_spacing, y_spacing, add_hex_text, custom_text_list, custom_text_color_list:
|
1050 |
+
gr.Warning("Please upload an Input Image to get started.") if input_image is None else hex_create(hex_size, border_size, input_image, start_x, start_y, end_x, end_y, rotation, background_color, background_opacity, border_color, border_opacity, fill_hex, color_display, filter_color, x_spacing, y_spacing, add_hex_text, custom_text_list, custom_text_color_list),
|
1051 |
+
inputs=[hex_size, border_size, input_image, start_x, start_y, end_x, end_y, rotation, background_color, background_opacity, border_color, border_opacity, fill_hex, color_display, filter_color, x_spacing, y_spacing, add_hex_text, custom_text_list, custom_text_color_list],
|
1052 |
+
outputs=[output_image, overlay_image],
|
1053 |
+
scroll_to_output=True
|
1054 |
+
)
|
1055 |
+
generate_input_image.click(
|
1056 |
+
fn=generate_input_image_click,
|
1057 |
+
inputs=[map_options, prompt_textbox, negative_prompt_textbox, model_textbox, randomize_seed, seed_slider, gr.State(False), gr.State(0.5), image_size_ratio],
|
1058 |
+
outputs=[input_image], scroll_to_output=True
|
1059 |
+
)
|
1060 |
+
# generate_depth_button.click(
|
1061 |
+
# fn=generate_depth_button_click,
|
1062 |
+
# inputs=[depth_image_source, voxel_size_factor, input_image, output_image, overlay_image, bordered_image_output],
|
1063 |
+
# outputs=[depth_map_output, model_output], scroll_to_output=True
|
1064 |
+
# )
|
1065 |
+
model_textbox.change(
|
1066 |
+
fn=update_prompt_notes,
|
1067 |
+
inputs=model_textbox,
|
1068 |
+
outputs=prompt_notes_label,preprocess=False
|
1069 |
+
)
|
1070 |
+
model_options.change(
|
1071 |
+
fn=lambda x: (gr.update(visible=(x == "Manual Entry")), gr.update(value=x) if x != "Manual Entry" else gr.update()),
|
1072 |
+
inputs=model_options,
|
1073 |
+
outputs=[model_textbox, model_textbox]
|
1074 |
+
)
|
1075 |
+
model_options.change(
|
1076 |
+
fn=update_prompt_notes,
|
1077 |
+
inputs=model_options,
|
1078 |
+
outputs=prompt_notes_label
|
1079 |
+
)
|
1080 |
+
composite_button.click(
|
1081 |
+
fn=lambda input_image, composite_color, composite_opacity: gr.Warning("Please upload an Input Image to get started.") if input_image is None else change_color(input_image, composite_color, composite_opacity),
|
1082 |
+
inputs=[input_image, composite_color, composite_opacity],
|
1083 |
+
outputs=[input_image]
|
1084 |
+
)
|
1085 |
|
1086 |
+
#use conditioned_image as the input_image for generate_input_image_click
|
1087 |
+
generate_input_image_from_gallery.click(
|
1088 |
+
fn=generate_input_image_click,
|
1089 |
+
inputs=[map_options, prompt_textbox, negative_prompt_textbox, model_textbox,randomize_seed, seed_slider, gr.State(True), image_guidance_stength, image_size_ratio],
|
1090 |
+
outputs=[input_image], scroll_to_output=True
|
1091 |
+
)
|
1092 |
|
1093 |
+
# Update the state variable with the prerendered image filepath when an image is selected
|
1094 |
+
prerendered_image_gallery.select(
|
1095 |
+
fn=on_prerendered_gallery_selection,
|
1096 |
+
inputs=None,
|
1097 |
+
outputs=[gr.State(current_prerendered_image)], # Update the state with the selected image
|
1098 |
+
show_api=False
|
1099 |
+
)
|
1100 |
+
# replace input image with selected gallery image
|
1101 |
+
replace_input_image_button.click(
|
1102 |
+
lambda: current_prerendered_image.value,
|
1103 |
+
inputs=None,
|
1104 |
+
outputs=[input_image], scroll_to_output=True
|
1105 |
+
)
|
1106 |
+
output_overlay_composite.change(
|
1107 |
+
fn=combine_images_with_lerp,
|
1108 |
+
inputs=[input_image, output_image, output_overlay_composite],
|
1109 |
+
outputs=[overlay_image], scroll_to_output=True
|
1110 |
+
)
|
1111 |
+
output_blend_multiply_composite.change(
|
1112 |
+
fn=multiply_and_blend_images,
|
1113 |
+
inputs=[input_image, output_image, output_blend_multiply_composite],
|
1114 |
+
outputs=[overlay_image],
|
1115 |
+
scroll_to_output=True
|
1116 |
+
)
|
1117 |
+
output_alpha_composite.change(
|
1118 |
+
fn=alpha_composite_with_control,
|
1119 |
+
inputs=[input_image, output_image, output_alpha_composite],
|
1120 |
+
outputs=[overlay_image],
|
1121 |
+
scroll_to_output=True
|
1122 |
+
)
|
1123 |
+
add_border_button.click(
|
1124 |
+
fn=lambda image_source, mask_w, mask_h, color, opacity, input_img, overlay_img: add_border(input_img if image_source == "Input Image" else overlay_img, mask_w, mask_h, update_color_opacity(detect_color_format(color), opacity * 2.55)),
|
1125 |
+
inputs=[border_image_source, mask_width, mask_height, margin_color, margin_opacity, input_image, overlay_image],
|
1126 |
+
outputs=[bordered_image_output],
|
1127 |
+
scroll_to_output=True
|
1128 |
+
)
|
1129 |
|
|
|
|
|
1130 |
|
1131 |
|
1132 |
+
#if __name__ == "__main__":
|
1133 |
+
logging.basicConfig(
|
1134 |
+
format="[%(levelname)s] %(asctime)s %(message)s", level=logging.INFO
|
1135 |
+
)
|
1136 |
+
logging.info("Environment Variables: %s" % os.environ)
|
1137 |
# if _get_output(["nvcc", "--version"]) is None:
|
1138 |
# logging.info("Installing CUDA toolkit...")
|
1139 |
# install_cuda_toolkit()
|
|
|
1143 |
# logging.info("Installing CUDA extensions...")
|
1144 |
# setup_runtime_env()
|
1145 |
#main(os.getenv("DEBUG") == "1")
|
1146 |
+
#main()
|
1147 |
+
|
1148 |
+
hexaGrid.queue(default_concurrency_limit=1,max_size=12,api_open=False)
|
1149 |
+
hexaGrid.launch(allowed_paths=["assets","/","./assets","images","./images", "./images/prerendered"], favicon_path="./assets/favicon.ico", max_file_size="10mb")
|
src/condition.py
CHANGED
@@ -1,4 +1,3 @@
|
|
1 |
-
import spaces
|
2 |
import gradio as gr
|
3 |
from torch import Tensor, ones_like
|
4 |
from typing import Optional, Union, List, Tuple
|
@@ -15,7 +14,7 @@ condition_dict = {
|
|
15 |
"deblurring": 7,
|
16 |
"fill": 9,
|
17 |
}
|
18 |
-
|
19 |
class Condition(object):
|
20 |
def __init__(
|
21 |
self,
|
|
|
|
|
1 |
import gradio as gr
|
2 |
from torch import Tensor, ones_like
|
3 |
from typing import Optional, Union, List, Tuple
|
|
|
14 |
"deblurring": 7,
|
15 |
"fill": 9,
|
16 |
}
|
17 |
+
|
18 |
class Condition(object):
|
19 |
def __init__(
|
20 |
self,
|