Delete app.py

app.py

@@ -1,213 +0,0 @@
-import gradio as gr
-import numpy as np
-import spaces
-import torch
-import random
-from PIL import Image
-
-from diffusers import FluxKontextPipeline
-from diffusers.utils import load_image
-from huggingface_hub import hf_hub_download
-
-MAX_SEED = np.iinfo(np.int32).max
-
-pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to("cuda")
-
-# Add all four adapters to the app with unique names
-pipe.load_lora_weights("prithivMLmods/PhotoCleanser-i2i", weight_name="PhotoCleanser-i2i.safetensors", adapter_name="cleanser")
-pipe.load_lora_weights("prithivMLmods/Photo-Restore-i2i", weight_name="Photo-Restore-i2i.safetensors", adapter_name="restorer")
-pipe.load_lora_weights("prithivMLmods/Polaroid-Warm-i2i", weight_name="Polaroid-Warm-i2i.safetensors", adapter_name="polaroid")
-pipe.load_lora_weights("prithivMLmods/Monochrome-Pencil", weight_name="Monochrome-Pencil-i2i.safetensors", adapter_name="pencil")
-
-
-@spaces.GPU
-def infer(input_image, prompt, lora_adapter, seed=42, randomize_seed=False, guidance_scale=2.5, steps=28, progress=gr.Progress(track_tqdm=True)):
-    """
-    Perform image editing using the FLUX.1 Kontext pipeline with a selected adapter.
-    
-    This function takes an input image, a text prompt, and a LoRA adapter choice to 
-    generate a modified version of the image.
-    
-    Args:
-        input_image (PIL.Image.Image): The input image to be edited.
-        prompt (str): Text description of the desired edit.
-        lora_adapter (str): The name of the LoRA adapter to use.
-        seed (int, optional): Random seed for reproducible generation. Defaults to 42.
-        randomize_seed (bool, optional): If True, generates a random seed. Defaults to False.
-        guidance_scale (float, optional): Controls adherence to the prompt. Defaults to 2.5.
-        steps (int, optional): Number of diffusion steps. Defaults to 28.
-        progress (gr.Progress, optional): Gradio progress tracker.
-    
-    Returns:
-        tuple: A 3-tuple containing the generated image, the seed used, and a Gradio
-               update to make the reuse button visible.
-    """
-    if lora_adapter == "PhotoCleanser":
-        pipe.set_adapters(["cleanser"], adapter_weights=[1.0])
-    elif lora_adapter == "PhotoRestorer":
-        pipe.set_adapters(["restorer"], adapter_weights=[1.0])
-    elif lora_adapter == "PolaroidWarm":
-        pipe.set_adapters(["polaroid"], adapter_weights=[1.0])
-    elif lora_adapter == "MonochromePencil":
-        pipe.set_adapters(["pencil"], adapter_weights=[1.0])
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    
-    if input_image:
-        input_image = input_image.convert("RGB")
-        image = pipe(
-            image=input_image, 
-            prompt=prompt,
-            guidance_scale=guidance_scale,
-            width = input_image.size[0],
-            height = input_image.size[1],
-            num_inference_steps=steps,
-            generator=torch.Generator().manual_seed(seed),
-        ).images[0]
-    else:
-        image = pipe(
-            prompt=prompt,
-            guidance_scale=guidance_scale,
-            num_inference_steps=steps,
-            generator=torch.Generator().manual_seed(seed),
-        ).images[0]
-    return image, seed, gr.Button(visible=True)
-
-@spaces.GPU
-def infer_example(input_image, prompt, lora_adapter):
-    """
-    Wrapper function for gr.Examples to call the main infer logic.
-    It unpacks the results to match the expected outputs of the Examples component.
-    """
-    image, seed, _ = infer(input_image, prompt, lora_adapter)
-    return image, seed
-
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 960px;
-}
-"""
-
-with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# **[Photo-Mate-i2i](https://huggingface.co/collections/prithivMLmods/i2i-kontext-exp-68ce573b5c0623476b636ec7)**
-        Image manipulation with Kontext adapters""")
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(label="Upload the image for editing", type="pil", height="300")
-                with gr.Row():
-                    prompt = gr.Text(
-                        label="Prompt",
-                        show_label=False,
-                        max_lines=1,
-                        placeholder="Enter your prompt for editing (e.g., 'Remove glasses', 'Add a hat')",
-                        container=False,
-                    )
-                    run_button = gr.Button("Run", scale=0)
-                with gr.Accordion("Advanced Settings", open=False):
-                    
-                    seed = gr.Slider(
-                        label="Seed",
-                        minimum=0,
-                        maximum=MAX_SEED,
-                        step=1,
-                        value=0,
-                    )
-                    
-                    randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                    
-                    guidance_scale = gr.Slider(
-                        label="Guidance Scale",
-                        minimum=1,
-                        maximum=10,
-                        step=0.1,
-                        value=2.5,
-                    )       
-                    
-                    steps = gr.Slider(
-                        label="Steps",
-                        minimum=1,
-                        maximum=30,
-                        value=28,
-                        step=1
-                    )
-                    
-            with gr.Column():
-                result = gr.Image(label="Result", show_label=False, interactive=False, format="png")
-                reuse_button = gr.Button("Reuse this image", visible=False)
-                with gr.Row():
-                    lora_adapter = gr.Dropdown(
-                    label="Choose Adapter",
-                    choices=["PhotoCleanser", "PhotoRestorer", "PolaroidWarm", "MonochromePencil"],
-                    value="PhotoCleanser"
-                )
-                    
-        # Consolidate all examples into a single component with a new "Selected LoRA" column
-        gr.Examples(
-            examples=[
-                [
-                    "photocleanser/1.png",
-                    "[photo content], remove the embroidered pattern from the image while preserving the background and remaining elements, maintaining realism and original details.",
-                    "PhotoCleanser"
-                ],
-                [
-                    "photocleanser/2.png",
-                    "[photo content], remove the cat from the image while preserving the background and remaining elements, maintaining realism and original details.",
-                    "PhotoCleanser"
-                ],
-                [
-                    "photorestore/1.png",
-                    "[photo content], restore and enhance the image by repairing any damage, scratches, or fading. Colorize the photo naturally while preserving authentic textures and details, maintaining a realistic and historically accurate look.",
-                    "PhotoRestorer"
-                ],
-                [
-                    "photorestore/2.png",
-                    "[photo content], restore and enhance the image by repairing any damage, scratches, or fading. Colorize the photo naturally while preserving authentic textures and details, maintaining a realistic and historically accurate look.",
-                    "PhotoRestorer"
-                ],
-                [
-                    "polaroid/1.png",
-                    "[photo content], apply a warm, vintage Polaroid-style filter, enhancing the image with nostalgic tones, soft focus, and characteristic light leaks for an authentic, retro feel.",
-                    "PolaroidWarm"
-                ],
-                [
-                    "polaroid/2.png",
-                    "[photo content], give the image a classic Polaroid look with warm, saturated colors, gentle fading, and a subtle vignette effect, evoking a sense of timeless memories.",
-                    "PolaroidWarm"
-                ],
-                [
-                    "pencil/1.png",
-                    "[photo content], transform the image into a detailed monochrome pencil sketch, emphasizing sharp lines, textures, and shading for a classic hand-drawn look.",
-                    "MonochromePencil"
-                ],
-                [
-                    "pencil/2.png",
-                    "[photo content], convert the photo into a realistic graphite pencil drawing, capturing the subject's form and depth with varied strokes and contrast.",
-                    "MonochromePencil"
-                ]
-            ],
-            # The inputs now include the lora_adapter dropdown
-            inputs=[input_image, prompt, lora_adapter],
-            outputs=[result, seed],
-            fn=infer_example,
-            cache_examples=False,
-            # Provide headers for clarity
-            label="Examples (Image | Prompt | Selected LoRA)"
-        )
-            
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
-        outputs = [result, seed, reuse_button]
-    )
-    reuse_button.click(
-        fn = lambda image: image,
-        inputs = [result],
-        outputs = [input_image]
-    )
-
-demo.launch(mcp_server=True)