revert my changes

app.py

@@ -3,137 +3,14 @@ import numpy as np
 import random
 import torch
 import spaces
-import os
-import json
-import torch
+
 from PIL import Image
-from qwenimage.pipeline_qwen_image_edit import QwenImageEditPipeline
-from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
-from huggingface_hub import InferenceClient
+import torch 
 import math
 
 from optimization import optimize_pipeline_
-
-# --- Prompt Enhancement using Hugging Face InferenceClient ---
-def polish_prompt_hf(original_prompt, system_prompt):
-    """
-    Rewrites the prompt using a Hugging Face InferenceClient.
-    """
-    # Ensure HF_TOKEN is set
-    api_key = os.environ.get("HF_TOKEN")
-    if not api_key:
-        print("Warning: HF_TOKEN not set. Falling back to original prompt.")
-        return original_prompt
-
-    try:
-        # Initialize the client
-        client = InferenceClient(
-            provider="cerebras",
-            api_key=api_key,
-        )
-
-        # Format the messages for the chat completions API
-        messages = [
-            {"role": "system", "content": system_prompt},
-            {"role": "user", "content": original_prompt}
-        ]
-
-        # Call the API
-        completion = client.chat.completions.create(
-            model="Qwen/Qwen3-235B-A22B-Instruct-2507",
-            messages=messages,
-        )
-        
-        # Parse the response
-        result = completion.choices[0].message.content
-        
-        # Try to extract JSON if present
-        if '{"Rewritten"' in result:
-            try:
-                # Clean up the response
-                result = result.replace('```json', '').replace('```', '')
-                result_json = json.loads(result)
-                polished_prompt = result_json.get('Rewritten', result)
-            except:
-                polished_prompt = result
-        else:
-            polished_prompt = result
-            
-        polished_prompt = polished_prompt.strip().replace("\n", " ")
-        return polished_prompt
-        
-    except Exception as e:
-        print(f"Error during API call to Hugging Face: {e}")
-        # Fallback to original prompt if enhancement fails
-        return original_prompt
-
-
-def polish_prompt(prompt, img):
-    """
-    Main function to polish prompts for image editing using HF inference.
-    """
-    SYSTEM_PROMPT = '''
-# Edit Instruction Rewriter
-You are a professional edit instruction rewriter. Your task is to generate a precise, concise, and visually achievable professional-level edit instruction based on the user-provided instruction and the image to be edited.  
-
-Please strictly follow the rewriting rules below:
-
-## 1. General Principles
-- Keep the rewritten prompt **concise**. Avoid overly long sentences and reduce unnecessary descriptive language.  
-- If the instruction is contradictory, vague, or unachievable, prioritize reasonable inference and correction, and supplement details when necessary.  
-- Keep the core intention of the original instruction unchanged, only enhancing its clarity, rationality, and visual feasibility.  
-- All added objects or modifications must align with the logic and style of the edited input image's overall scene.  
-
-## 2. Task Type Handling Rules
-### 1. Add, Delete, Replace Tasks
-- If the instruction is clear (already includes task type, target entity, position, quantity, attributes), preserve the original intent and only refine the grammar.  
-- If the description is vague, supplement with minimal but sufficient details (category, color, size, orientation, position, etc.). For example:  
-    > Original: "Add an animal"  
-    > Rewritten: "Add a light-gray cat in the bottom-right corner, sitting and facing the camera"  
-- Remove meaningless instructions: e.g., "Add 0 objects" should be ignored or flagged as invalid.  
-- For replacement tasks, specify "Replace Y with X" and briefly describe the key visual features of X.  
-
-### 2. Text Editing Tasks
-- All text content must be enclosed in English double quotes " ". Do not translate or alter the original language of the text, and do not change the capitalization.  
-- **For text replacement tasks, always use the fixed template:**
-    - Replace "xx" to "yy".  
-    - Replace the xx bounding box to "yy".  
-- If the user does not specify text content, infer and add concise text based on the instruction and the input image's context. For example:  
-    > Original: "Add a line of text" (poster)  
-    > Rewritten: "Add text "LIMITED EDITION" at the top center with slight shadow"  
-- Specify text position, color, and layout in a concise way.  
-
-### 3. Human Editing Tasks
-- Maintain the person's core visual consistency (ethnicity, gender, age, hairstyle, expression, outfit, etc.).  
-- If modifying appearance (e.g., clothes, hairstyle), ensure the new element is consistent with the original style.  
-- **For expression changes, they must be natural and subtle, never exaggerated.**  
-- If deletion is not specifically emphasized, the most important subject in the original image (e.g., a person, an animal) should be preserved.
-    - For background change tasks, emphasize maintaining subject consistency at first.  
-- Example:  
-    > Original: "Change the person's hat"  
-    > Rewritten: "Replace the man's hat with a dark brown beret; keep smile, short hair, and gray jacket unchanged"  
-
-### 4. Style Transformation or Enhancement Tasks
-- If a style is specified, describe it concisely with key visual traits. For example:  
-    > Original: "Disco style"  
-    > Rewritten: "1970s disco: flashing lights, disco ball, mirrored walls, colorful tones"  
-- If the instruction says "use reference style" or "keep current style," analyze the input image, extract main features (color, composition, texture, lighting, art style), and integrate them concisely.  
-- **For coloring tasks, including restoring old photos, always use the fixed template:** "Restore old photograph, remove scratches, reduce noise, enhance details, high resolution, realistic, natural skin tones, clear facial features, no distortion, vintage photo restoration"  
-- If there are other changes, place the style description at the end.
-
-## 3. Rationality and Logic Checks
-- Resolve contradictory instructions: e.g., "Remove all trees but keep all trees" should be logically corrected.  
-- Add missing key information: if position is unspecified, choose a reasonable area based on composition (near subject, empty space, center/edges).  
-
-# Output Format
-Return only the rewritten instruction text directly, without JSON formatting or any other wrapper.
-'''
-    
-    # Note: We're not actually using the image in the HF version, 
-    # but keeping the interface consistent
-    full_prompt = f"{SYSTEM_PROMPT}\n\nUser Input: {prompt}\n\nRewritten Prompt:"
-    
-    return polish_prompt_hf(full_prompt, SYSTEM_PROMPT)
+from qwenimage.pipeline_qwen_image_edit import QwenImageEditPipeline
+from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
 
 
 # --- Model Loading ---
@@ -148,7 +25,7 @@ optimize_pipeline_(pipe, image=Image.new("RGB", (1024, 1024)), prompt="prompt")
 # --- UI Constants and Helpers ---
 MAX_SEED = np.iinfo(np.int32).max
 
-# --- Main Inference Function ---
+# --- Main Inference Function (with hardcoded negative prompt) ---
 @spaces.GPU(duration=120)
 def infer(
     image,
@@ -156,14 +33,13 @@ def infer(
     seed=42,
     randomize_seed=False,
     true_guidance_scale=4.0,
-    num_inference_steps=30, 
-    rewrite_prompt=True,
+    num_inference_steps=50,
     progress=gr.Progress(track_tqdm=True),
 ):
     """
-    Generates an edited image using the Qwen-Image-Edit pipeline with Lightning acceleration.
+    Generates an image using the local Qwen-Image diffusers pipeline.
     """
-    # Hardcode the negative prompt as in the original
+    # Hardcode the negative prompt as requested
     negative_prompt = " "
     
     if randomize_seed:
@@ -172,83 +48,54 @@ def infer(
     # Set up the generator for reproducibility
     generator = torch.Generator(device=device).manual_seed(seed)
     
-    print(f"Original prompt: '{prompt}'")
+    print(f"Calling pipeline with prompt: '{prompt}'")
     print(f"Negative Prompt: '{negative_prompt}'")
-    print(f"Seed: {seed}, Steps: {num_inference_steps}, Guidance: {true_guidance_scale}")
-    
-    if rewrite_prompt:
-        prompt = polish_prompt(prompt, image)
-        print(f"Rewritten Prompt: {prompt}")
-
-    # Generate the edited image - always generate just 1 image
+    print(f"Seed: {seed}, Steps: {num_inference_steps}, Guidance: {guidance_scale}")
 
-    images = pipe(
+    # Generate the image
+    image = pipe(
         image,
         prompt=prompt,
         negative_prompt=negative_prompt,
         num_inference_steps=num_inference_steps,
         generator=generator,
         true_cfg_scale=true_guidance_scale,
-        num_images_per_prompt=1  # Always generate only 1 image
-    ).images
-    
-    # Return the first (and only) image
-    return images[0], seed
-    
+    ).images[0]
 
+    return image, seed
 
 # --- Examples and UI Layout ---
+examples = []
 
 css = """
 #col-container {
     margin: 0 auto;
     max-width: 1024px;
 }
-#logo-title {
-    text-align: center;
-}
-#logo-title img {
-    width: 400px;
-}
 #edit_text{margin-top: -62px !important}
 """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.HTML("""
-        <div id="logo-title">
-            <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_edit_logo.png" alt="Qwen-Image Edit Logo" width="400" style="display: block; margin: 0 auto;">
-        </div>
-        """)
-        gr.Markdown("""
-        [Learn more](https://github.com/QwenLM/Qwen-Image) about the Qwen-Image series. 
-        Try on [Qwen Chat](https://chat.qwen.ai/), or [download model](https://huggingface.co/Qwen/Qwen-Image-Edit) to run locally with ComfyUI or diffusers.
-        """)
-        
+        gr.HTML('<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_logo.png" alt="Qwen-Image Logo" width="400" style="display: block; margin: 0 auto;">')
+        gr.HTML('<h1 style="text-align: center;margin-left: 80px;color: #5b47d1;font-style: italic;">Edit</h1>', elem_id="edit_text")
+        gr.Markdown("[Learn more](https://github.com/QwenLM/Qwen-Image) about the Qwen-Image series. Try on [Qwen Chat](https://chat.qwen.ai/), or [download model](https://huggingface.co/Qwen/Qwen-Image-Edit) to run locally with ComfyUI or diffusers.")
         with gr.Row():
             with gr.Column():
-                input_image = gr.Image(
-                    label="Input Image", 
-                    show_label=True, 
-                    type="pil"
+                input_image = gr.Image(label="Input Image", show_label=False, type="pil")
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    placeholder="describe the edit instruction",
+                    container=False,
                 )
-            # Changed from Gallery to Image
-            result = gr.Image(
-                label="Result", 
-                show_label=True, 
-                type="pil"
-            )
-            
-        with gr.Row():
-            prompt = gr.Text(
-                label="Edit Instruction",
-                show_label=False,
-                placeholder="Describe the edit instruction (e.g., 'Replace the background with a sunset', 'Add a red hat', 'Remove the person')",
-                container=False,
-            )
-            run_button = gr.Button("Edit!", variant="primary")
+                run_button = gr.Button("Edit!", variant="primary")
+
+            result = gr.Image(label="Result", show_label=False, type="pil")
 
         with gr.Accordion("Advanced Settings", open=False):
+            # Negative prompt UI element is removed here
+
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,
@@ -260,29 +107,24 @@ with gr.Blocks(css=css) as demo:
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
 
             with gr.Row():
+
                 true_guidance_scale = gr.Slider(
                     label="True guidance scale",
                     minimum=1.0,
                     maximum=10.0,
                     step=0.1,
-                    value=4.0
+                    value=1.0
                 )
 
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
-                    minimum=4,
+                    minimum=1,
                     maximum=50,
                     step=1,
-                    value=30
+                    value=50,
                 )
-                
-            # Removed num_images_per_prompt slider entirely
-            rewrite_prompt = gr.Checkbox(
-                label="Enhance prompt (using HF Inference)", 
-                value=True
-            )
 
-        #gr.Examples(examples=[["qwen-image.png", "make her eyes brown"]], inputs=[input_image, prompt], outputs=[result, seed], fn=infer, cache_examples="lazy")
+        # gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=False)
 
     gr.on(
         triggers=[run_button.click, prompt.submit],
@@ -290,12 +132,11 @@ with gr.Blocks(css=css) as demo:
         inputs=[
             input_image,
             prompt,
+            # negative_prompt is no longer an input from the UI
             seed,
             randomize_seed,
             true_guidance_scale,
             num_inference_steps,
-            rewrite_prompt,
-            # Removed num_images_per_prompt from inputs
         ],
         outputs=[result, seed],
     )