Upload folder using huggingface_hub

.env

@@ -0,0 +1,5 @@
+# Add your Gemini API key here
+GOOGLE_API_KEY=AIzaSyCVzRDxkuvtaS1B22F_F-zl0ehhXR0nuU8
+
+GEMINI_API_KEY=AIzaSyCVzRDxkuvtaS1B22F_F-zl0ehhXR0nuU8
+

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+data/1.jpg filter=lfs diff=lfs merge=lfs -text
+data/1777043.jpg filter=lfs diff=lfs merge=lfs -text
+data/2807615.jpg filter=lfs diff=lfs merge=lfs -text

.gradio/cached_examples/17/log.csv

@@ -0,0 +1,7 @@
+Enhanced Smile Result,Processing Status,timestamp
+"[{""image"": {""path"": "".gradio/cached_examples/17/Enhanced Smile Result/297e6826d707efe59e6e/image.webp"", ""url"": ""/gradio_api/file=/private/var/folders/k9/4nnkrkrs3sb3t80c0120tpl80000gr/T/gradio/e6f72632b86ca0f8af6c79451b685aa7b63f0403c3a6651387a5adfdab8b73f0/image.webp"", ""size"": null, ""orig_name"": null, ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}, ""caption"": null}]",Note: The model returned a text response instead of an enhanced image: ,2025-04-16 14:42:18.166586
+"[{""image"": {""path"": "".gradio/cached_examples/17/Enhanced Smile Result/63258dc188ae831c8922/image.webp"", ""url"": ""/gradio_api/file=/private/var/folders/k9/4nnkrkrs3sb3t80c0120tpl80000gr/T/gradio/b8cc3be88c50956dd06137dca273308c19d6d827dfcee57cdc68fbc10ad2894d/image.webp"", ""size"": null, ""orig_name"": null, ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}, ""caption"": null}]","Note: The model returned a text response instead of an enhanced image: I
+ cannot fulfill your request to modify the provided image. The image contains text and does
+ not depict a person's face or teeth that can be enhanced with smile enhancement
+ techniques.
+",2025-04-16 14:42:22.984487

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----
+MIIFazCCA1OgAwIBAgIRAIIQz7DSQONZRGPgu2OCiwAwDQYJKoZIhvcNAQELBQAw
+TzELMAkGA1UEBhMCVVMxKTAnBgNVBAoTIEludGVybmV0IFNlY3VyaXR5IFJlc2Vh
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+TkXWStAmzOVyyghqpZXjFaH3pO3JLF+l+/+sKAIuvtd7u+Nxe5AW0wdeRlN8NwdC
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+mRGunUHBcnWEvgJBQl9nJEiU0Zsnvgc/ubhPgXRR4Xq37Z0j4r7g1SgEEzwxA57d
+emyPxgcYxn/eR44/KJ4EBs+lVDR3veyJm+kXQ99b21/+jh5Xos1AnX5iItreGCc=
+-----END CERTIFICATE-----

README.md

@@ -1,12 +1,31 @@
 ---
-title: Smile Enhancement Ai
-emoji: 🌖
-colorFrom: purple
-colorTo: green
+title: smile-enhancement-ai
+emoji: 😁
+colorFrom: indigo
+colorTo: blue
 sdk: gradio
-sdk_version: 5.25.2
+sdk_version: 5.20.1
 app_file: app.py
-pinned: false
+pinned: true
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Smile Enhancement AI
+
+A simple, user-friendly application that uses Google's Gemini AI to enhance smiles in portrait photos. The app creates natural-looking smile enhancements with adjustable intensity levels.
+
+## Features
+
+- Simple upload interface - just drag and drop your photo
+- Creates personalized, natural-looking smiles that suit the individual
+- Preserves natural dental characteristics while making subtle enhancements
+- Maintains each person's unique smile features and tooth coloration
+- Enhances eye crinkles and cheek raising for authentic expressions
+- Preserves facial identity while enhancing smiles
+- Works with most portrait photos showing visible teeth
+- No API key or login required
+
+## Usage
+
+1. Upload a clear selfie with a visible smile
+2. Click "Enhance Smile with Natural Expressions" to process your image
+3. Download your enhanced smile image

app.py

@@ -0,0 +1,314 @@
+import json
+import os
+import time
+import uuid
+import tempfile
+from PIL import Image, ImageDraw, ImageFont
+import gradio as gr
+import base64
+import mimetypes
+
+from google import genai
+from google.genai import types
+
+def save_binary_file(file_name, data):
+    with open(file_name, "wb") as f:
+        f.write(data)
+
+def generate(text, file_name, api_key, model="gemini-2.0-flash-exp"):
+    # Initialize client using provided api_key (or fallback to env variable)
+    client = genai.Client(api_key=(api_key.strip() if api_key and api_key.strip() != ""
+                                     else os.environ.get("GEMINI_API_KEY")))
+    
+    try:
+        print("Uploading file to Gemini API...")
+        files = [ client.files.upload(file=file_name) ]
+        
+        contents = [
+            types.Content(
+                role="user",
+                parts=[
+                    types.Part.from_uri(
+                        file_uri=files[0].uri,
+                        mime_type=files[0].mime_type,
+                    ),
+                    types.Part.from_text(text=text),
+                ],
+            ),
+        ]
+        generate_content_config = types.GenerateContentConfig(
+            temperature=0,  # Lower temperature for more consistent, conservative results
+            top_p=0.92,
+            max_output_tokens=8192,
+            response_modalities=["image", "text"],
+            response_mime_type="text/plain",
+            # Additional parameters to encourage subtle, natural results
+            safety_settings=[
+                {
+                    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+                }
+            ]
+        )
+
+        text_response = ""
+        image_path = None
+        # Create a temporary file to potentially store image data
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            temp_path = tmp.name
+            print("Sending request to Gemini API...")
+            # Add a timeout to prevent indefinite waiting
+            start_time = time.time()
+            max_wait_time = 60  # Maximum wait time in seconds
+            
+            try:
+                stream = client.models.generate_content_stream(
+                    model=model,
+                    contents=contents,
+                    config=generate_content_config,
+                )
+                
+                for chunk in stream:
+                    # Check for timeout
+                    if time.time() - start_time > max_wait_time:
+                        print("Gemini API request timed out after", max_wait_time, "seconds")
+                        break
+                        
+                    if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
+                        continue
+                    candidate = chunk.candidates[0].content.parts[0]
+                    # Check for inline image data
+                    if candidate.inline_data:
+                        save_binary_file(temp_path, candidate.inline_data.data)
+                        print(f"Smile enhancement image generated: {temp_path}")
+                        image_path = temp_path
+                        # If an image is found, we assume that is the desired output.
+                        break
+                    else:
+                        # Accumulate text response if no inline_data is present.
+                        text_response += chunk.text + "\n"
+                        print("Received text response from Gemini API")
+            except Exception as e:
+                print(f"Error during content generation: {str(e)}")
+                # Continue with the function, returning empty responses
+    except Exception as e:
+        print(f"Error in Gemini API setup: {str(e)}")
+        return None, f"Error: {str(e)}"
+    finally:
+        # Always clean up files
+        try:
+            if 'files' in locals() and files:
+                del files
+        except:
+            pass
+            
+    return image_path, text_response
+
+def assess_image_quality(original_image, enhanced_image):
+    """
+    Assesses the quality of the enhanced image based on specific criteria.
+    Returns a tuple of (is_acceptable, feedback_message)
+    """
+    try:
+        # Check if enhanced image exists
+        if enhanced_image is None:
+            return False, "No enhanced image generated"
+        
+        # Image dimension checks
+        if enhanced_image.size[0] < 100 or enhanced_image.size[1] < 100:
+            return False, "Enhanced image appears to be too small or improperly sized"
+            
+        # Check that the enhanced image has similar dimensions to the original
+        # This helps ensure facial proportions are maintained
+        width_diff = abs(original_image.size[0] - enhanced_image.size[0])
+        height_diff = abs(original_image.size[1] - enhanced_image.size[1])
+        
+        # If dimensions are significantly different, it suggests the image proportions changed
+        if width_diff > 20 or height_diff > 20:
+            return False, "Enhanced image dimensions differ significantly from original, suggesting facial proportions may have changed"
+        
+        # Check image has proper RGB channels for natural skin tones
+        if enhanced_image.mode != 'RGB':
+            return False, "Enhanced image does not have the correct color mode"
+        
+        # For now, we'll do basic checks and assume the model follows guidelines
+        return True, "Image passes quality assessment criteria"
+    except Exception as e:
+        print(f"Error in quality assessment: {str(e)}")
+        # Default to not accepting the image if assessment fails
+        return False, f"Assessment error: {str(e)}"
+
+def process_smile_enhancement(input_image, max_attempts=2):
+    try:
+        if input_image is None:
+            return None, "", ""
+            
+        # Get API key from environment variable
+        gemini_api_key = "AIzaSyCVzRDxkuvtaS1B22F_F-zl0ehhXR0nuU8"
+        if not gemini_api_key:
+            print("Error: GEMINI_API_KEY not found in environment variables")
+            return [input_image], "", "API key not configured"
+            
+        # Save the input image to a temporary file
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            input_path = tmp.name
+            input_image.save(input_path)
+            print(f"Input image saved to {input_path}")
+            
+        # Initialize attempt counter and result variables    
+        current_attempt = 0
+        result_img = None
+        feedback_history = []
+        max_processing_time = 120  # Maximum time in seconds for overall processing
+        start_processing_time = time.time()
+        
+        while current_attempt < max_attempts:
+            # Check if overall processing time exceeded
+            if time.time() - start_processing_time > max_processing_time:
+                print(f"Overall processing time exceeded {max_processing_time} seconds")
+                break
+                
+            current_attempt += 1
+            print(f"Starting processing attempt {current_attempt}/{max_attempts}...")
+            
+            # Create a comprehensive prompt for true smile enhancement that affects facial features naturally
+            # Adjust prompt based on previous attempts if needed
+            prompt = """
+            Create a naturally enhanced smile that suits this specific person's face and character. Make the following personalized improvements:
+            
+            - Slightly enhance the existing teeth while PRESERVING their natural color, spacing, and individual characteristics
+            - DO NOT make teeth perfectly white or perfectly aligned - keep some natural variation and character
+            - Create subtle, natural smile lines around the eyes (crow's feet) appropriate for this person's age and face
+            - Slightly raise the cheeks WITHOUT widening the face
+            - Add a slight narrowing of the eyes that happens in genuine smiles
+            - Create subtle dimples ONLY if they already exist in the original image
+            - Enhance the overall joyful expression while maintaining the person's unique facial structure
+            
+            IMPORTANT GUIDELINES:
+            - PRESERVE THE PERSON'S NATURAL DENTAL CHARACTERISTICS - teeth should still look like THEIR teeth, just slightly enhanced
+            - Keep teeth coloration natural and appropriate for the person - avoid unnaturally white teeth
+            - Maintain slight natural imperfections in tooth alignment that give character to the smile
+            - Create a genuine, authentic-looking smile that affects the entire face naturally
+            - ABSOLUTELY CRITICAL: DO NOT widen the face or change face width at all
+            - Preserve the person's identity completely (extremely important)
+            - Preserve exact facial proportions and face width of the original image
+            - Maintain natural-looking results appropriate for the person's age and face structure
+            - Keep teeth proportionate to the face - avoid making them too large or prominent
+            - Maintain proper tooth-to-face ratio and ensure teeth fit naturally within the mouth
+            - Keep the original background, lighting, and image quality intact
+            - Ensure the enhanced smile looks natural, genuine, and believable
+            - Create a smile that looks like a moment of true happiness for THIS specific person
+            - Remember that not everyone has or wants perfect white teeth - the enhancements should SUIT THE INDIVIDUAL
+            - If teeth are enhanced, maintain their natural characteristics while making subtle improvements
+            """
+            
+            # If not the first attempt, add previous feedback to the prompt
+            if current_attempt > 1 and feedback_history:
+                prompt += """
+                
+                IMPORTANT FEEDBACK FROM PREVIOUS ATTEMPT:
+                """ + " ".join(feedback_history) + """
+                Please address these issues in this new attempt.
+                """
+            
+            # Process silently
+            print(f"Processing attempt {current_attempt}/{max_attempts}...")
+            
+            # Set timeout for individual API call
+            api_call_timeout = time.time() + 45  # 45 second timeout for API call
+            
+            try:
+                # Process the image using Google's Gemini model with timeout
+                image_path, text_response = generate(text=prompt, file_name=input_path, api_key=gemini_api_key)
+                
+                # Check if API call timeout occurred
+                if time.time() > api_call_timeout:
+                    print("API call timeout occurred")
+                    feedback_history.append("API call timed out, trying again with simplified request.")
+                    continue
+                    
+                print(f"API response received: Image path: {image_path is not None}, Text length: {len(text_response)}")
+                
+                if image_path:
+                    # Load and convert the image if needed
+                    try:
+                        result_img = Image.open(image_path)
+                        if result_img.mode == "RGBA":
+                            result_img = result_img.convert("RGB")
+                        
+                        print("Successfully loaded generated image")
+                        
+                        # Assess the quality of the enhanced image
+                        is_acceptable, assessment_feedback = assess_image_quality(input_image, result_img)
+                        print(f"Image quality assessment: {is_acceptable}, {assessment_feedback}")
+                        
+                        if is_acceptable:
+                            # Return the enhanced image with success message
+                            success_message = "Successfully loaded generated image\nImage quality assessment: True, Image passes quality assessment criteria"
+                            return [result_img], "", success_message
+                        else:
+                            # Image didn't pass quality assessment, add feedback for next attempt
+                            feedback_history.append(assessment_feedback)
+                            
+                            # If we've reached max attempts, return the best result so far
+                            if current_attempt >= max_attempts:
+                                print("Max attempts reached, returning best result")
+                                return [result_img], "", ""
+                    except Exception as img_error:
+                        print(f"Error processing the generated image: {str(img_error)}")
+                        feedback_history.append(f"Error with image: {str(img_error)}")
+                else:
+                    # No image was generated, only text response
+                    print("No image was generated, only text response")
+                    feedback_history.append("No image was generated in the previous attempt.")
+                    
+                    # If we've reached max attempts, return the original image
+                    if current_attempt >= max_attempts:
+                        print("Max attempts reached, returning original image")
+                        return [input_image], "", ""
+            except Exception as gen_error:
+                print(f"Error during generation attempt {current_attempt}: {str(gen_error)}")
+                feedback_history.append(f"Error during processing: {str(gen_error)}")
+                
+                # If we've reached max attempts, return the original image
+                if current_attempt >= max_attempts:
+                    return [input_image], "", ""
+        
+        # Return the original image as a fallback without messages
+        print("Returning original image as fallback")
+        return [input_image], "", ""
+    except Exception as e:
+        # Return the original image silently on error
+        print(f"Overall error in process_smile_enhancement: {str(e)}")
+        return [input_image], "", ""
+
+# Create a clean interface with minimal UI elements and no settings/deployment info
+with gr.Blocks(title="Smile Enhancement", css="footer {visibility: hidden} .gradio-container {min-height: 0 !important}") as demo:
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(
+                type="pil",
+                label=None,
+                image_mode="RGB",
+                elem_classes="upload-box"
+            )
+            
+            submit_btn = gr.Button("Enhance Smile with Natural Expressions", elem_classes="generate-btn")
+        
+        with gr.Column():
+            output_gallery = gr.Gallery(label=None)
+            
+            # Simplify feedback to minimize UI elements
+            feedback_text = gr.Textbox(label=None, visible=True, elem_classes="status-box")
+            
+            # Hidden element for structure
+            output_text = gr.Textbox(visible=False)
+    
+    submit_btn.click(
+        fn=process_smile_enhancement,
+        inputs=[image_input],
+        outputs=[output_gallery, output_text, feedback_text]
+    )
+
+# Launch the app without showing Gradio branding or share links
+demo.queue(max_size=50).launch(show_api=False, show_error=False)

requirements.txt

@@ -0,0 +1,4 @@
+google-genai
+gradio
+pydantic
+python-dotenv