from PIL.ImageOps import colorize, scale import gradio as gr import importlib import sys import os from matplotlib.pyplot import step from model_args import segtracker_args,sam_args,aot_args from SegTracker import SegTracker # sys.path.append('.') # sys.path.append('..') import cv2 from PIL import Image from skimage.morphology.binary import binary_dilation import argparse import torch import time from seg_track_anything import aot_model2ckpt, tracking_objects_in_video, draw_mask import gc import numpy as np import json from tool.transfer_tools import mask2bbox def clean(): return None, None, None, None, None, None, [[], []] def get_click_prompt(click_stack, point): click_stack[0].append(point["coord"]) click_stack[1].append(point["mode"] ) prompt = { "points_coord":click_stack[0], "points_mode":click_stack[1], "multimask":"True", } return prompt def get_meta_from_video(input_video): if input_video is None: return None, None, None, "" print("get meta information of input video") cap = cv2.VideoCapture(input_video) _, first_frame = cap.read() cap.release() first_frame = cv2.cvtColor(first_frame, cv2.COLOR_BGR2RGB) return first_frame, first_frame, first_frame, "" def get_meta_from_img_seq(input_img_seq): if input_img_seq is None: return None, None, None, "" print("get meta information of img seq") # Create dir file_name = input_img_seq.name.split('/')[-1].split('.')[0] file_path = f'./assets/{file_name}' if os.path.isdir(file_path): os.system(f'rm -r {file_path}') os.makedirs(file_path) # Unzip file os.system(f'unzip {input_img_seq.name} -d ./assets ') imgs_path = sorted([os.path.join(file_path, img_name) for img_name in os.listdir(file_path)]) first_frame = imgs_path[0] first_frame = cv2.imread(first_frame) first_frame = cv2.cvtColor(first_frame, cv2.COLOR_BGR2RGB) return first_frame, first_frame, first_frame def SegTracker_add_first_frame(Seg_Tracker, origin_frame, predicted_mask): with torch.cuda.amp.autocast(): # Reset the first frame's mask frame_idx = 0 Seg_Tracker.restart_tracker() Seg_Tracker.add_reference(origin_frame, predicted_mask, frame_idx) Seg_Tracker.first_frame_mask = predicted_mask return Seg_Tracker def init_SegTracker(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame): if origin_frame is None: return None, origin_frame, [[], []], "" # reset aot args aot_args["model"] = aot_model aot_args["model_path"] = aot_model2ckpt[aot_model] aot_args["long_term_mem_gap"] = long_term_mem aot_args["max_len_long_term"] = max_len_long_term # reset sam args segtracker_args["sam_gap"] = sam_gap segtracker_args["max_obj_num"] = max_obj_num sam_args["generator_args"]["points_per_side"] = points_per_side Seg_Tracker = SegTracker(segtracker_args, sam_args, aot_args) Seg_Tracker.restart_tracker() return Seg_Tracker, origin_frame, [[], []], "" def init_SegTracker_Stroke(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame): if origin_frame is None: return None, origin_frame, [[], []], origin_frame # reset aot args aot_args["model"] = aot_model aot_args["model_path"] = aot_model2ckpt[aot_model] aot_args["long_term_mem_gap"] = long_term_mem aot_args["max_len_long_term"] = max_len_long_term # reset sam args segtracker_args["sam_gap"] = sam_gap segtracker_args["max_obj_num"] = max_obj_num sam_args["generator_args"]["points_per_side"] = points_per_side Seg_Tracker = SegTracker(segtracker_args, sam_args, aot_args) Seg_Tracker.restart_tracker() return Seg_Tracker, origin_frame, [[], []], origin_frame def undo_click_stack_and_refine_seg(Seg_Tracker, origin_frame, click_stack, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side): if Seg_Tracker is None: return Seg_Tracker, origin_frame, [[], []] print("Undo!") if len(click_stack[0]) > 0: click_stack[0] = click_stack[0][: -1] click_stack[1] = click_stack[1][: -1] if len(click_stack[0]) > 0: prompt = { "points_coord":click_stack[0], "points_mode":click_stack[1], "multimask":"True", } masked_frame = seg_acc_click(Seg_Tracker, prompt, origin_frame) return Seg_Tracker, masked_frame, click_stack else: return Seg_Tracker, origin_frame, [[], []] def seg_acc_click(Seg_Tracker, prompt, origin_frame): # seg acc to click predicted_mask, masked_frame = Seg_Tracker.seg_acc_click( origin_frame=origin_frame, coords=np.array(prompt["points_coord"]), modes=np.array(prompt["points_mode"]), multimask=prompt["multimask"], ) Seg_Tracker = SegTracker_add_first_frame(Seg_Tracker, origin_frame, predicted_mask) return masked_frame def sam_click(Seg_Tracker, origin_frame, point_mode, click_stack, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, evt:gr.SelectData): """ Args: origin_frame: nd.array click_stack: [[coordinate], [point_mode]] """ print("Click") if point_mode == "Positive": point = {"coord": [evt.index[0], evt.index[1]], "mode": 1} else: # TODO：add everything positive points point = {"coord": [evt.index[0], evt.index[1]], "mode": 0} if Seg_Tracker is None: Seg_Tracker, _, _, _ = init_SegTracker(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame) # get click prompts for sam to predict mask click_prompt = get_click_prompt(click_stack, point) # Refine acc to prompt masked_frame = seg_acc_click(Seg_Tracker, click_prompt, origin_frame) return Seg_Tracker, masked_frame, click_stack def sam_stroke(Seg_Tracker, origin_frame, drawing_board, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side): if Seg_Tracker is None: Seg_Tracker, _ , _, _ = init_SegTracker(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame) print("Stroke") mask = drawing_board["mask"] bbox = mask2bbox(mask[:, :, 0]) # bbox: [[x0, y0], [x1, y1]] predicted_mask, masked_frame = Seg_Tracker.seg_acc_bbox(origin_frame, bbox) Seg_Tracker = SegTracker_add_first_frame(Seg_Tracker, origin_frame, predicted_mask) return Seg_Tracker, masked_frame, origin_frame def gd_detect(Seg_Tracker, origin_frame, grounding_caption, box_threshold, text_threshold, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side): if Seg_Tracker is None: Seg_Tracker, _ , _, _ = init_SegTracker(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame) print("Detect") predicted_mask, annotated_frame= Seg_Tracker.detect_and_seg(origin_frame, grounding_caption, box_threshold, text_threshold) Seg_Tracker = SegTracker_add_first_frame(Seg_Tracker, origin_frame, predicted_mask) masked_frame = draw_mask(annotated_frame, predicted_mask) return Seg_Tracker, masked_frame, origin_frame def segment_everything(Seg_Tracker, aot_model, long_term_mem, max_len_long_term, origin_frame, sam_gap, max_obj_num, points_per_side): if Seg_Tracker is None: Seg_Tracker, _ , _, _ = init_SegTracker(aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame) print("Everything") frame_idx = 0 with torch.cuda.amp.autocast(): pred_mask = Seg_Tracker.seg(origin_frame) torch.cuda.empty_cache() gc.collect() Seg_Tracker.add_reference(origin_frame, pred_mask, frame_idx) Seg_Tracker.first_frame_mask = pred_mask masked_frame = draw_mask(origin_frame.copy(), pred_mask) return Seg_Tracker, masked_frame def add_new_object(Seg_Tracker): prev_mask = Seg_Tracker.first_frame_mask Seg_Tracker.update_origin_merged_mask(prev_mask) Seg_Tracker.curr_idx += 1 print("Ready to add new object!") return Seg_Tracker, [[], []] def tracking_objects(Seg_Tracker, input_video, input_img_seq, fps): print("Start tracking !") return tracking_objects_in_video(Seg_Tracker, input_video, input_img_seq, fps) def seg_track_app(): ########################################################## ###################### Front-end ######################## ########################################################## app = gr.Blocks() with app: gr.Markdown( '''
Segmentation for Swallowing Diseases )
''' ) click_stack = gr.State([[],[]]) # Storage clicks status origin_frame = gr.State(None) Seg_Tracker = gr.State(None) aot_model = gr.State(None) sam_gap = gr.State(None) points_per_side = gr.State(None) max_obj_num = gr.State(None) with gr.Row(): # video input with gr.Column(scale=0.5): tab_video_input = gr.Tab(label="Video type input") with tab_video_input: input_video = gr.Video(label='Input video').style(height=550) tab_img_seq_input = gr.Tab(label="Image-Seq type input") with tab_img_seq_input: with gr.Row(): input_img_seq = gr.File(label='Input Image-Seq').style(height=550) with gr.Column(scale=0.25): extract_button = gr.Button(value="extract") fps = gr.Slider(label='fps', minimum=5, maximum=50, value=8, step=1) input_first_frame = gr.Image(label='Segment result of first frame',interactive=True).style(height=550) tab_everything = gr.Tab(label="Everything") with tab_everything: with gr.Row(): seg_every_first_frame = gr.Button(value="Segment everything for first frame", interactive=True) point_mode = gr.Radio( choices=["Positive"], value="Positive", label="Point Prompt", interactive=True) every_undo_but = gr.Button( value="Undo", interactive=True ) # every_reset_but = gr.Button( # value="Reset", # interactive=True # ) tab_click = gr.Tab(label="Click") with tab_click: with gr.Row(): point_mode = gr.Radio( choices=["Positive", "Negative"], value="Positive", label="Point Prompt", interactive=True) # args for modify and tracking click_undo_but = gr.Button( value="Undo", interactive=True ) # click_reset_but = gr.Button( # value="Reset", # interactive=True # ) tab_stroke = gr.Tab(label="Stroke") with tab_stroke: drawing_board = gr.Image(label='Drawing Board', tool="sketch", brush_radius=10, interactive=True) with gr.Row(): seg_acc_stroke = gr.Button(value="Segment", interactive=True) # stroke_reset_but = gr.Button( # value="Reset", # interactive=True # ) tab_text = gr.Tab(label="Text") with tab_text: grounding_caption = gr.Textbox(label="Detection Prompt") detect_button = gr.Button(value="Detect") with gr.Accordion("Advanced options", open=False): with gr.Row(): with gr.Column(scale=0.5): box_threshold = gr.Slider( label="Box Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.001 ) with gr.Column(scale=0.5): text_threshold = gr.Slider( label="Text Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.001 ) with gr.Row(): with gr.Column(scale=0.5): with gr.Tab(label="SegTracker Args"): # args for tracking in video do segment-everthing points_per_side = gr.Slider( label = "points_per_side", minimum= 1, step = 1, maximum=100, value=16, interactive=True ) sam_gap = gr.Slider( label='sam_gap', minimum = 1, step=1, maximum = 9999, value=100, interactive=True, ) max_obj_num = gr.Slider( label='max_obj_num', minimum = 50, step=1, maximum = 300, value=255, interactive=True ) with gr.Accordion("aot advanced options", open=False): aot_model = gr.Dropdown( label="aot_model", choices = [ "deaotb", "deaotl", "r50_deaotl" ], value = "r50_deaotl", interactive=True, ) long_term_mem = gr.Slider(label="long term memory gap", minimum=1, maximum=9999, value=9999, step=1) max_len_long_term = gr.Slider(label="max len of long term memory", minimum=1, maximum=9999, value=9999, step=1) with gr.Column(): new_object_button = gr.Button( value="Add new object", interactive=True ) reset_button = gr.Button( value="Reset", interactive=True, ) track_for_video = gr.Button( value="Start Tracking", interactive=True, ) with gr.Column(scale=0.5): output_video = gr.Video(label='Output video').style(height=550) output_mask = gr.File(label="Predicted masks") ########################################################## ###################### back-end ######################### ########################################################## # listen to the input_video to get the first frame of video input_video.change( fn=get_meta_from_video, inputs=[ input_video ], outputs=[ input_first_frame, origin_frame, drawing_board, grounding_caption ] ) # listen to the input_img_seq to get the first frame of video input_img_seq.change( fn=get_meta_from_img_seq, inputs=[ input_img_seq ], outputs=[ input_first_frame, origin_frame, drawing_board, grounding_caption ] ) #-------------- Input compont ------------- tab_video_input.select( fn = clean, inputs=[], outputs=[ input_video, input_img_seq, Seg_Tracker, input_first_frame, origin_frame, drawing_board, click_stack, ] ) tab_img_seq_input.select( fn = clean, inputs=[], outputs=[ input_video, input_img_seq, Seg_Tracker, input_first_frame, origin_frame, drawing_board, click_stack, ] ) extract_button.click( fn=get_meta_from_img_seq, inputs=[ input_img_seq ], outputs=[ input_first_frame, origin_frame, drawing_board ] ) # ------------------- Interactive component ----------------- # listen to the tab to init SegTracker tab_everything.select( fn=init_SegTracker, inputs=[ aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame ], outputs=[ Seg_Tracker, input_first_frame, click_stack, grounding_caption ], queue=False, ) tab_click.select( fn=init_SegTracker, inputs=[ aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame ], outputs=[ Seg_Tracker, input_first_frame, click_stack, grounding_caption ], queue=False, ) tab_stroke.select( fn=init_SegTracker_Stroke, inputs=[ aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame, ], outputs=[ Seg_Tracker, input_first_frame, click_stack, drawing_board ], queue=False, ) tab_text.select( fn=init_SegTracker, inputs=[ aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame ], outputs=[ Seg_Tracker, input_first_frame, click_stack, grounding_caption ], queue=False, ) # Use SAM to segment everything for the first frame of video seg_every_first_frame.click( fn=segment_everything, inputs=[ Seg_Tracker, aot_model, long_term_mem, max_len_long_term, origin_frame, sam_gap, max_obj_num, points_per_side, ], outputs=[ Seg_Tracker, input_first_frame, ], ) # Interactively modify the mask acc click input_first_frame.select( fn=sam_click, inputs=[ Seg_Tracker, origin_frame, point_mode, click_stack, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, ], outputs=[ Seg_Tracker, input_first_frame, click_stack ] ) # Interactively segment acc stroke seg_acc_stroke.click( fn=sam_stroke, inputs=[ Seg_Tracker, origin_frame, drawing_board, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, ], outputs=[ Seg_Tracker, input_first_frame, drawing_board ] ) # Use grounding-dino to detect object detect_button.click( fn=gd_detect, inputs=[ Seg_Tracker, origin_frame, grounding_caption, box_threshold, text_threshold, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side ], outputs=[ Seg_Tracker, input_first_frame ] ) # Add new object new_object_button.click( fn=add_new_object, inputs= [ Seg_Tracker ], outputs= [ Seg_Tracker, click_stack ] ) # Track object in video track_for_video.click( fn=tracking_objects, inputs=[ Seg_Tracker, input_video, input_img_seq, fps, ], outputs=[ output_video, output_mask ] ) # ----------------- Reset and Undo --------------------------- # Rest reset_button.click( fn=init_SegTracker, inputs=[ aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, origin_frame ], outputs=[ Seg_Tracker, input_first_frame, click_stack, grounding_caption ], queue=False, show_progress=False ) # every_reset_but.click( # fn=init_SegTracker, # inputs=[ # aot_model, # sam_gap, # max_obj_num, # points_per_side, # origin_frame # ], # outputs=[ # Seg_Tracker, input_first_frame, click_stack, grounding_caption # ], # queue=False, # show_progress=False # ) # click_reset_but.click( # fn=init_SegTracker, # inputs=[ # aot_model, # sam_gap, # max_obj_num, # points_per_side, # origin_frame # ], # outputs=[ # Seg_Tracker, input_first_frame, click_stack, grounding_caption # ], # queue=False, # show_progress=False # ) # stroke_reset_but.click( # fn=init_SegTracker_Stroke, # inputs=[ # aot_model, # sam_gap, # max_obj_num, # points_per_side, # origin_frame, # ], # outputs=[ # Seg_Tracker, input_first_frame, click_stack, drawing_board # ], # queue=False, # show_progress=False # ) # Undo click click_undo_but.click( fn = undo_click_stack_and_refine_seg, inputs=[ Seg_Tracker, origin_frame, click_stack, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, ], outputs=[ Seg_Tracker, input_first_frame, click_stack ] ) every_undo_but.click( fn = undo_click_stack_and_refine_seg, inputs=[ Seg_Tracker, origin_frame, click_stack, aot_model, long_term_mem, max_len_long_term, sam_gap, max_obj_num, points_per_side, ], outputs=[ Seg_Tracker, input_first_frame, click_stack ] ) with gr.Tab(label='Video example'): gr.Examples( examples=[ # os.path.join(os.path.dirname(__file__), "assets", "840_iSXIa0hE8Ek.mp4"), os.path.join(os.path.dirname(__file__), "assets", "blackswan.mp4"), # os.path.join(os.path.dirname(__file__), "assets", "bear.mp4"), # os.path.join(os.path.dirname(__file__), "assets", "camel.mp4"), # os.path.join(os.path.dirname(__file__), "assets", "skate-park.mp4"), # os.path.join(os.path.dirname(__file__), "assets", "swing.mp4"), ], inputs=[input_video], ) with gr.Tab(label='Image-seq expamle'): gr.Examples( examples=[ os.path.join(os.path.dirname(__file__), "assets", "840_iSXIa0hE8Ek.zip"), ], inputs=[input_img_seq], ) app.queue(concurrency_count=1) app.launch(debug=True, enable_queue=True) if __name__ == "__main__": seg_track_app()