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README.md

@@ -1,13 +1,13 @@
 ---
 title: FLUX Kontext LoRA Gallery
-emoji: 📚
+emoji: 😄
 colorFrom: purple
-colorTo: blue
+colorTo: red
 sdk: gradio
-sdk_version: 5.38.0
+sdk_version: 4.42.0
 app_file: app.py
 pinned: false
-short_description: Image editing  with Kontext LoRAs
+license: other
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import os
+import gradio as gr
+import json
+import logging
+import torch
+from PIL import Image
+import spaces
+from diffusers import FluxKontextPipeline
+
+from huggingface_hub import HfFileSystem, ModelCard
+import copy
+import random
+import time
+
+import subprocess
+subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+
+from huggingface_hub import login
+hf_token = os.environ.get("HF_TOKEN_GATED")
+login(token=hf_token)
+
+# Load LoRAs from JSON file
+with open('loras.json', 'r') as f:
+    loras = json.load(f)
+
+# Initialize the base model
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+base_model = "black-forest-labs/FLUX.1-Kontext-dev"
+
+pipe = FluxKontextPipeline.from_pretrained(base_model, torch_dtype=dtype).to(device)
+
+MAX_SEED = 2**32-1
+
+class calculateDuration:
+    def __init__(self, activity_name=""):
+        self.activity_name = activity_name
+
+    def __enter__(self):
+        self.start_time = time.time()
+        return self
+    
+    def __exit__(self, exc_type, exc_value, traceback):
+        self.end_time = time.time()
+        self.elapsed_time = self.end_time - self.start_time
+        if self.activity_name:
+            print(f"Elapsed time for {self.activity_name}: {self.elapsed_time:.6f} seconds")
+        else:
+            print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
+
+def update_selection(evt: gr.SelectData, default_scale, lora_scale):
+    selected_lora = loras[evt.index]
+    new_placeholder = f"Type a prompt for {selected_lora['title']}"
+    prompt = selected_lora["prompt"]
+    lora_repo = selected_lora["repo"]
+    updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✨"
+    if default_scale:
+        lora_scale = selected_lora["lora_scale"]
+    return (
+        prompt,
+        updated_text,
+        evt.index,
+        lora_scale,
+    )
+
+@spaces.GPU
+def generate_image(input_image, prompt_mash, steps, seed, cfg_scale, lora_scale, progress):
+    pipe.to("cuda")
+    generator = torch.Generator(device="cuda").manual_seed(seed)
+    with calculateDuration("Generating image"):
+        # Generate image
+        for img in pipe(
+            image=input_image,
+            prompt=prompt_mash,
+            num_inference_steps=steps,
+            guidance_scale=cfg_scale,
+            generator=generator,
+            joint_attention_kwargs={"scale": lora_scale},
+            output_type="pil",
+        ):
+            yield img
+
+@spaces.GPU
+def run_lora(input_image, prompt, cfg_scale, steps, selected_index, randomize_seed, seed, lora_scale, progress=gr.Progress(track_tqdm=True)):
+    if selected_index is None:
+        raise gr.Error("You must select a LoRA before proceeding.")
+    selected_lora = loras[selected_index]
+    lora_path = selected_lora["repo"]
+    trigger_word = selected_lora["trigger_word"]
+    if(trigger_word):
+        if "trigger_position" in selected_lora:
+            if selected_lora["trigger_position"] == "prepend" and trigger_word != prompt:
+                prompt_mash = f"{trigger_word} {prompt}"
+            else:
+                if trigger_word != prompt:
+                    prompt_mash = f"{prompt} {trigger_word}"
+                else:
+                    prompt_mash = prompt
+        else:
+            prompt_mash = f"{trigger_word} {prompt}"
+    else:
+        prompt_mash = prompt
+
+    with calculateDuration("Unloading LoRA"):
+        pipe.unload_lora_weights()
+        
+    # Load LoRA weights
+    with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
+        if "weights" in selected_lora:
+            pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
+        else:
+            pipe.load_lora_weights(lora_path)
+
+    # Set random seed for reproducibility
+    with calculateDuration("Randomizing seed"):
+        if randomize_seed:
+            seed = random.randint(0, MAX_SEED)
+
+    image_generator = generate_image(input_image, prompt_mash, steps, seed, cfg_scale, lora_scale, progress)
+    
+    # Consume the generator to get the final image
+    final_image = None
+    step_counter = 0
+    for image in image_generator:
+        step_counter+=1
+        final_image = image
+        progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
+        yield image, seed, gr.update(value=progress_bar, visible=True)
+        
+    yield final_image, seed, gr.update(value=progress_bar, visible=False)
+
+css = '''
+#gen_btn{height: 100%}
+#title{text-align: center}
+#title h1{font-size: 3em; display:inline-flex; align-items:center}
+#title img{width: 100px; margin-right: 0.5em}
+#gallery .grid-wrap{height: 10vh}
+#lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
+.card_internal{display: flex;height: 100px;margin-top: .5em}
+.card_internal img{margin-right: 1em}
+.styler{--form-gap-width: 0px !important}
+#progress{height:30px}
+#progress .generating{display:none}
+.progress-container {width: 100%;height: 30px;background-color: #f0f0f0;border-radius: 15px;overflow: hidden;margin-bottom: 20px}
+.progress-bar {height: 100%;background-color: #4f46e5;width: calc(var(--current) / var(--total) * 100%);transition: width 0.5s ease-in-out}
+'''
+with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
+    title = gr.HTML(
+        """<h1><img src="https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-collections/resolve/main/logo.png" alt="LoRA"> FLUX Kontext LoRA Gallery from Shakker AI</h1>""",
+        elem_id="title",
+    )
+    selected_index = gr.State(None)
+    with gr.Row():
+        with gr.Column(scale=3):
+            prompt = gr.Textbox(label="Prompt", lines=1, placeholder="Type a prompt after selecting a LoRA")
+        with gr.Column(scale=1, elem_id="gen_column"):
+            generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
+    with gr.Row():
+        with gr.Column():
+            selected_info = gr.Markdown("")
+            gallery = gr.Gallery(
+                [(item["image"], item["title"]) for item in loras],
+                label="LoRA Gallery",
+                allow_preview=False,
+                columns=3,
+                elem_id="gallery"
+            )
+    with gr.Row():
+        with gr.Column():
+            image_in = gr.Image(label="Upload the image for editing", type="pil")
+        
+        with gr.Column():
+            progress_bar = gr.Markdown(elem_id="progress",visible=False)
+            result = gr.Image(label="Generated Image")
+
+    with gr.Row():
+        with gr.Accordion("Advanced Settings", open=False):
+            with gr.Column():
+                with gr.Row():
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=2.5)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
+                
+                with gr.Row():
+                    randomize_seed = gr.Checkbox(True, label="Randomize seed")
+                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
+
+                    default_scale = gr.Checkbox(True, label="Use default LoRA scale")
+                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=3, step=0.01, value=1.0)
+
+    gallery.select(
+        update_selection,
+        inputs=[default_scale, lora_scale],
+        outputs=[prompt, selected_info, selected_index, lora_scale]
+    )
+    gr.on(
+        triggers=[generate_button.click, prompt.submit],
+        fn=run_lora,
+        inputs=[image_in, prompt, cfg_scale, steps, selected_index, randomize_seed, seed, lora_scale],
+        outputs=[result, seed, progress_bar]
+    )
+
+app.queue()
+app.launch()

loras.json

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+[
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Sketch-Style/resolve/main/images/example1.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Sketch-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Sketch-Style",
+    "trigger_word": "convert this image into sketches",
+    "prompt": "convert this image into sketches",
+    "lora_scale": 1.0
+  },
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style/resolve/main/images/example1.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style",
+    "trigger_word": "Convert to a flat cartoon style while keeping the subject unchanged",
+    "prompt": "Convert to a flat cartoon style while keeping the subject unchanged",
+    "lora_scale": 1.0
+  },
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Illustration-Style/resolve/main/images/example3.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Illustration-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Illustration-Style",
+    "trigger_word": "change to illustration style",
+    "prompt": "change to illustration style",
+    "lora_scale": 1.0
+  },
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Pixel-Style/resolve/main/images/example1.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Pixel-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Pixel-Style",
+    "trigger_word": "Convert to a pixel art style",
+    "prompt": "Convert to a pixel art style",
+    "lora_scale": 1.0
+  },
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Felt-Style/resolve/main/images/example1.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Felt-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Felt-Style",
+    "trigger_word": "Turned into a plush felt toy",
+    "prompt": "Turned into a plush felt toy",
+    "lora_scale": 1.0
+  },
+  {
+    "image": "https://huggingface.co/Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Bioluminescence-Style/resolve/main/images/example1.png",
+    "title": "FLUX.1-Kontext-dev-LoRA-Bioluminescence-Style",
+    "repo": "Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Bioluminescence-Style",
+    "trigger_word": "bioluminescence efficiency",
+    "prompt": "The edges of the character's body emit a dazzling light effect.",
+    "lora_scale": 1.0
+  }
+]

requirements.txt

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+git+https://github.com/huggingface/diffusers.git
+torch
+torchvision
+transformers
+einops
+spaces
+accelerate
+omegaconf
+huggingface-hub
+opencv-python
+sentencepiece
+peft
+scipy
+scikit-image
+numpy
+gradio==4.32.0
+pydantic==2.9.0