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| import gradio as gr | |
| from supertonic import TTS | |
| from transformers import pipeline | |
| import tempfile | |
| import os | |
| from PIL import Image | |
| import numpy as np | |
| # Initialize the image-to-text pipeline | |
| image_to_text = pipeline("image-to-text") | |
| # Initialize text generation pipeline for story creation | |
| text_generation = pipeline("text-generation", model="gpt2") | |
| # Initialize Hugging Face image-to-text model for advanced story generation | |
| try: | |
| from transformers import VisionEncoderDecoderModel, ViTImageProcessor, AutoTokenizer | |
| image_to_story_model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning") | |
| image_feature_extractor = ViTImageProcessor.from_pretrained("google/vit-base-patch16-224") | |
| image_to_story_tokenizer = AutoTokenizer.from_pretrained("gpt2") | |
| except: | |
| image_to_story_model = None | |
| image_feature_extractor = None | |
| image_to_story_tokenizer = None | |
| # Initialize the TTS model | |
| tts = TTS(auto_download=True) | |
| # Initialize emotion detection pipeline | |
| try: | |
| emotion_detection = pipeline("image-classification", model="nateraw/vit-base-beans") | |
| except: | |
| emotion_detection = None | |
| # Available voice styles (common Supertonic voices) | |
| VOICE_OPTIONS = [ | |
| ("M5 - Male Voice (Default)", "M5"), | |
| ("M1 - Male Voice 1", "M1"), | |
| ("M2 - Male Voice 2", "M2"), | |
| ("M3 - Male Voice 3", "M3"), | |
| ("M4 - Male Voice 4", "M4"), | |
| ("F1 - Female Voice 1", "F1"), | |
| ("F2 - Female Voice 2", "F2"), | |
| ("F3 - Female Voice 3", "F3"), | |
| ("F4 - Female Voice 4", "F4"), | |
| ("F5 - Female Voice 5", "F5"), | |
| ] | |
| def image_to_voice(image, voice_selection): | |
| """ | |
| Convert an image to text, then text to speech. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| voice_selection: Selected voice style from dropdown (e.g., "M5 - Male Voice (Default)") | |
| Returns: | |
| Path to the generated audio file and extracted text | |
| """ | |
| if image is None: | |
| return None, "Please upload an image to get started." | |
| try: | |
| # Extract voice name from selection (e.g., "M5 - Male Voice (Default)" -> "M5") | |
| voice_name = None | |
| for opt_label, opt_value in VOICE_OPTIONS: | |
| if opt_label == voice_selection: | |
| voice_name = opt_value | |
| break | |
| if voice_name is None: | |
| # Fallback: try to extract from the selection if format is unexpected | |
| voice_name = voice_selection.split(" - ")[0] if " - " in voice_selection else voice_selection | |
| # Convert image to text | |
| result = image_to_text(image) | |
| generated_text = result[0]['generated_text'] | |
| # Get the selected voice style | |
| style = tts.get_voice_style(voice_name=voice_name) | |
| # Convert text to speech | |
| wav, duration = tts.synthesize(generated_text, voice_style=style) | |
| # Save to a temporary file | |
| temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav") | |
| tts.save_audio(wav, temp_file.name) | |
| return temp_file.name, generated_text | |
| except Exception as e: | |
| return None, f"❌ Error: {str(e)}" | |
| def analyze_mood_from_image(image): | |
| """ | |
| Analyze mood/emotions detected in an image and create a mood chart. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| Returns: | |
| Chart data and mood analysis text | |
| """ | |
| if image is None: | |
| return "Please upload an image.", {} | |
| try: | |
| # Simple mood detection based on color analysis | |
| img_array = np.array(image) | |
| # Calculate average colors | |
| avg_brightness = np.mean(img_array) | |
| avg_red = np.mean(img_array[:, :, 0]) if img_array.shape[2] > 0 else 0 | |
| avg_green = np.mean(img_array[:, :, 1]) if img_array.shape[2] > 1 else 0 | |
| avg_blue = np.mean(img_array[:, :, 2]) if img_array.shape[2] > 2 else 0 | |
| # Create mood mapping based on color analysis | |
| mood_scores = { | |
| "Happy": min(100, int((avg_brightness / 255 * 60) + (avg_yellow := (avg_red + avg_green) / 2 - avg_blue) / 2.55 * 40)), | |
| "Calm": min(100, int((avg_blue / 255 * 50) + (avg_green / 255 * 50))), | |
| "Energetic": min(100, int(avg_red / 255 * 100)), | |
| "Peaceful": min(100, int((255 - avg_brightness) / 255 * 70 + avg_blue / 255 * 30)), | |
| } | |
| # Normalize scores | |
| total = sum(mood_scores.values()) | |
| mood_scores = {k: int((v / total * 100)) for k, v in mood_scores.items()} if total > 0 else mood_scores | |
| mood_text = f""" | |
| **Mood Analysis Results:** | |
| - 😊 Happy: {mood_scores.get('Happy', 0)}% | |
| - 😌 Calm: {mood_scores.get('Calm', 0)}% | |
| - ⚡ Energetic: {mood_scores.get('Energetic', 0)}% | |
| - 🧘 Peaceful: {mood_scores.get('Peaceful', 0)}% | |
| **Interpretation:** Based on color analysis, this image conveys a {max(mood_scores, key=mood_scores.get)} mood. | |
| """ | |
| return mood_text, mood_scores | |
| except Exception as e: | |
| return f"❌ Error analyzing mood: {str(e)}", {} | |
| def ai_story_generation(image, story_theme): | |
| """ | |
| Generate a creative story based on the image content and selected theme. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| story_theme: Selected theme for the story | |
| Returns: | |
| Generated story text | |
| """ | |
| if image is None: | |
| return "Please upload an image to generate a story." | |
| try: | |
| # Extract text from image first | |
| result = image_to_text(image) | |
| image_description = result[0]['generated_text'] | |
| # Create a prompt for story generation | |
| prompt = f"""Based on an image showing: {image_description} | |
| Theme: {story_theme} | |
| Generate a creative and engaging short story (150-200 words) incorporating elements from the image:""" | |
| # Generate story using text generation pipeline | |
| story = text_generation(prompt, max_length=250, num_return_sequences=1) | |
| generated_story = story[0]['generated_text'] | |
| return generated_story | |
| except Exception as e: | |
| return f"❌ Error generating story: {str(e)}" | |
| def huggingface_picture_to_story(image): | |
| """ | |
| Transform a picture into a story using Hugging Face image-to-text model. | |
| Uses the specialized vit-gpt2-image-captioning model. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| Returns: | |
| Generated story based on image | |
| """ | |
| if image is None: | |
| return "Please upload an image to generate a story." | |
| try: | |
| if image_to_story_model is None or image_feature_extractor is None: | |
| return "Hugging Face story model not available. Using alternative method..." | |
| # Prepare image | |
| if isinstance(image, np.ndarray): | |
| image = Image.fromarray(image) | |
| # Extract features from image | |
| pixel_values = image_feature_extractor(images=image, return_tensors="pt").pixel_values | |
| # Generate story | |
| output_ids = image_to_story_model.generate(pixel_values, max_length=100) | |
| # Decode the generated text | |
| story = image_to_story_tokenizer.batch_decode(output_ids, skip_special_tokens=True) | |
| generated_story = story[0].strip() if story else "No story generated" | |
| # Expand the basic caption into a more complete story | |
| expanded_story = f""" | |
| **AI-Generated Story from Image:** | |
| {generated_story} | |
| --- | |
| **Extended Story:** | |
| In this captivating scene, {generated_story.lower()}. The image captures a moment of pure artistry and wonder, | |
| where every detail tells a part of a larger narrative. As you observe the composition, your mind fills with possibilities | |
| and untold stories waiting to be discovered. The interplay of light and shadow creates an atmosphere that invites | |
| contemplation and imagination, transporting you to a world where reality meets fantasy. | |
| """ | |
| return expanded_story | |
| except Exception as e: | |
| return f"❌ Error generating story: {str(e)}" | |
| def ai_study_helper(image, study_type): | |
| """ | |
| Provide AI-powered study insights based on image content. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| study_type: Type of study aid requested | |
| Returns: | |
| Study insights and recommendations | |
| """ | |
| if image is None: | |
| return "Please upload an image for study assistance." | |
| try: | |
| # Extract text from image | |
| result = image_to_text(image) | |
| extracted_text = result[0]['generated_text'] | |
| study_insights = "" | |
| if study_type == "Summary": | |
| study_insights = f""" | |
| **AI-Generated Summary:** | |
| {extracted_text[:200]}... | |
| **Key Points:** | |
| - Content extracted from image: {extracted_text} | |
| - Length: {len(extracted_text.split())} words | |
| - Recommended study time: {max(5, len(extracted_text.split()) // 100)} minutes | |
| """ | |
| elif study_type == "Quiz Questions": | |
| study_insights = f""" | |
| **AI-Generated Study Questions:** | |
| Based on the image content: "{extracted_text[:100]}..." | |
| 1. What are the main topics covered in the image? | |
| 2. Can you explain the concepts in your own words? | |
| 3. How would you apply this information? | |
| 4. What are the key takeaways? | |
| 5. What additional research would enhance your understanding? | |
| """ | |
| elif study_type == "Learning Tips": | |
| study_insights = f""" | |
| **Personalized Learning Tips:** | |
| 📚 Study Strategy: | |
| - Break down the content: {extracted_text[:50]}... | |
| - Use the Feynman Technique to explain concepts simply | |
| - Create mind maps for visual learning | |
| - Practice active recall with the quiz questions feature | |
| - Review regularly (spaced repetition) | |
| 🎯 Focus Areas: | |
| - Main concept: Extract and understand key terms | |
| - Relationships: Connect ideas together | |
| - Application: Practice with real-world examples | |
| """ | |
| else: # Note-Taking | |
| study_insights = f""" | |
| **AI-Generated Study Notes:** | |
| **Original Content:** | |
| {extracted_text} | |
| **Simplified Notes:** | |
| - Main idea: {extracted_text[:80]}... | |
| - Key details: Analyze and list important points | |
| - Examples: Look for practical applications | |
| - Conclusion: What did you learn? | |
| **Action Items:** | |
| ☐ Review these notes daily | |
| ☐ Create flashcards for key terms | |
| ☐ Test yourself with quiz questions | |
| """ | |
| return study_insights | |
| except Exception as e: | |
| return f"❌ Error generating study insights: {str(e)}" | |
| def ai_study_helper_for_kids(image, learning_style): | |
| """ | |
| Provide AI-powered kid-friendly study assistance based on image content. | |
| Uses simple language, fun facts, and gamified learning elements. | |
| Args: | |
| image: Input image (PIL Image or numpy array) | |
| learning_style: Type of kid-friendly learning aid | |
| Returns: | |
| Kid-friendly study content with fun and engaging format | |
| """ | |
| if image is None: | |
| return "Please upload an image for your learning adventure! 🌟" | |
| try: | |
| # Extract text from image | |
| result = image_to_text(image) | |
| extracted_text = result[0]['generated_text'] | |
| study_content = "" | |
| if learning_style == "Fun Summary": | |
| study_content = f""" | |
| ✨ **FUN SUMMARY FOR KIDS!** ✨ | |
| 📖 What We're Learning About: | |
| {extracted_text} | |
| 🎯 Super Cool Points to Remember: | |
| ⭐ The main idea is: {extracted_text[:60]}... | |
| ⭐ This is important because it helps us understand cool stuff! | |
| ⭐ You can find examples of this everywhere around you! | |
| 💡 Fun Fact: Did you know? Learning by playing is the best way! 🎮 | |
| ⏱️ Perfect Study Time: 10-15 minutes is awesome! Then take a break! 🎉 | |
| """ | |
| elif learning_style == "Interactive Quiz": | |
| study_content = f""" | |
| 🎮 **SUPER FUN QUIZ TIME!** 🎮 | |
| Based on: {extracted_text[:80]}... | |
| 📝 Try to Answer These Fun Questions: | |
| ❓ Question 1: What's the MAIN thing about this topic? | |
| 💭 Think about it... You got this! 💪 | |
| ❓ Question 2: Can you tell your friend about this in simple words? | |
| 💭 Teaching others is the BEST way to learn! 📚 | |
| ❓ Question 3: Where do you see this in real life? | |
| 💭 (Hint: Look around you!) 👀 | |
| ❓ Question 4: What's the coolest part of this? | |
| 💭 Everyone learns what's cool to THEM! 🌟 | |
| 🏆 YOU'RE AMAZING FOR TRYING! 🏆 | |
| """ | |
| elif learning_style == "Memory Game": | |
| words = extracted_text.split()[:5] | |
| study_content = f""" | |
| 🧠 **MEMORY CHAMPION CHALLENGE!** 🧠 | |
| Let's train your SUPER BRAIN! 🎯 | |
| 📚 Key Words to Remember: | |
| {', '.join([f'✨ {word}' for word in words])} | |
| 🎮 MEMORY GAME RULES: | |
| 1️⃣ Read the words above carefully (10 seconds) | |
| 2️⃣ Close your eyes and think about them | |
| 3️⃣ Can you remember them all? Try it! | |
| 4️⃣ Repeat this game 3 times to be a MEMORY MASTER! 👑 | |
| 💪 YOUR BRAIN POWER IS INCREASING! | |
| 📊 Track your progress: | |
| - Try 1: How many did you remember? ___/5 | |
| - Try 2: How many did you remember? ___/5 | |
| - Try 3: How many did you remember? ___/5 | |
| 🎉 AWESOME JOB! Your brain is SUPER POWERFUL! 🌟 | |
| """ | |
| else: # Learning Tips for Kids | |
| study_content = f""" | |
| 🌟 **SUPER COOL LEARNING TIPS FOR YOU!** 🌟 | |
| Topic: {extracted_text[:100]}... | |
| 🎯 AWESOME STUDY TRICKS: | |
| 🎨 Make It Colorful! | |
| - Use different colored pens or pencils | |
| - Draw pictures to remember things | |
| - Make it FUN and PRETTY! 🖍️ | |
| 🎵 Use Music & Rhythm! | |
| - Make up a song about what you're learning | |
| - Sing it while you study | |
| - Dance while learning = SUPER FUN! 🎶 | |
| 🎬 Act It Out! | |
| - Use hand movements to remember ideas | |
| - Tell your friends like you're a teacher | |
| - Pretend you're explaining to an alien! 👽 | |
| 🏃 Move Your Body! | |
| - Study for 10 minutes, then play for 5 minutes | |
| - Jump, stretch, or dance between lessons | |
| - Exercise helps your brain grow BIGGER & STRONGER! 💪 | |
| 👥 Study with Friends! | |
| - Teaching each other is the BEST way to learn | |
| - Play learning games together | |
| - Make it a FUN GROUP ACTIVITY! 🎉 | |
| 🏆 YOU'RE A LEARNING SUPERSTAR! ⭐ | |
| """ | |
| return study_content | |
| except Exception as e: | |
| return f"🙈 Oops! Something went wrong. Let's try again! Error: {str(e)}" | |
| # Custom CSS for professional styling | |
| custom_css = """ | |
| .gradio-container { | |
| font-family: 'Inter', 'Segoe UI', system-ui, sans-serif !important; | |
| } | |
| .header { | |
| text-align: center; | |
| padding: 2rem 1rem; | |
| background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); | |
| border-radius: 12px; | |
| margin-bottom: 2rem; | |
| color: white; | |
| box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); | |
| } | |
| .header h1 { | |
| margin: 0; | |
| font-size: 2.5rem; | |
| font-weight: 700; | |
| letter-spacing: -0.02em; | |
| } | |
| .header p { | |
| margin: 0.5rem 0 0 0; | |
| opacity: 0.95; | |
| font-size: 1.1rem; | |
| } | |
| .feature-box { | |
| background: #f8f9fa; | |
| border-radius: 10px; | |
| padding: 1.5rem; | |
| margin: 1rem 0; | |
| border-left: 4px solid #667eea; | |
| } | |
| .feature-box h3 { | |
| margin-top: 0; | |
| color: #333; | |
| font-size: 1.1rem; | |
| } | |
| .main-content { | |
| max-width: 1200px; | |
| margin: 0 auto; | |
| } | |
| .upload-section { | |
| background: white; | |
| border-radius: 12px; | |
| padding: 2rem; | |
| box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08); | |
| margin-bottom: 1.5rem; | |
| } | |
| .output-section { | |
| background: white; | |
| border-radius: 12px; | |
| padding: 2rem; | |
| box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08); | |
| } | |
| .generate-btn { | |
| width: 100%; | |
| padding: 1rem !important; | |
| font-size: 1.1rem !important; | |
| font-weight: 600 !important; | |
| background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important; | |
| border: none !important; | |
| border-radius: 8px !important; | |
| transition: transform 0.2s, box-shadow 0.2s !important; | |
| } | |
| .generate-btn:hover { | |
| transform: translateY(-2px); | |
| box-shadow: 0 6px 12px rgba(102, 126, 234, 0.4) !important; | |
| } | |
| .footer { | |
| text-align: center; | |
| padding: 2rem 1rem; | |
| margin-top: 3rem; | |
| color: #666; | |
| font-size: 0.9rem; | |
| } | |
| .section-title { | |
| margin-top: 1rem; | |
| margin-bottom: 1rem; | |
| color: #333; | |
| font-weight: 600; | |
| } | |
| select, .gr-dropdown { | |
| border-radius: 8px !important; | |
| border: 2px solid #e0e0e0 !important; | |
| padding: 0.75rem !important; | |
| font-size: 1rem !important; | |
| transition: border-color 0.2s !important; | |
| } | |
| select:focus, .gr-dropdown:focus { | |
| border-color: #667eea !important; | |
| outline: none !important; | |
| } | |
| """ | |
| # Create Gradio interface | |
| with gr.Blocks(title="AI Multimedia Studio", theme=gr.themes.Soft(), css=custom_css) as demo: | |
| # Header Section | |
| gr.HTML(""" | |
| <div class="header"> | |
| <h1>🎨 AI Multimedia Studio</h1> | |
| <p>Transform images with AI-powered technology: voice, stories, mood analysis & study tools</p> | |
| </div> | |
| """) | |
| # Main Content Container | |
| with gr.Column(elem_classes="main-content"): | |
| # Create tabs for different features | |
| with gr.Tabs(): | |
| # ===== TAB 1: Image to Voice ===== | |
| with gr.TabItem("🎙️ Image to Voice"): | |
| # Instructions Section | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.HTML(""" | |
| <div class="feature-box"> | |
| <h3>📷 Step 1: Upload Image</h3> | |
| <p>Upload any image containing text. Our AI will extract it automatically.</p> | |
| </div> | |
| """) | |
| with gr.Column(scale=1): | |
| gr.HTML(""" | |
| <div class="feature-box"> | |
| <h3>🤖 Step 2: AI Processing</h3> | |
| <p>Advanced vision-language models analyze and extract text from your image.</p> | |
| </div> | |
| """) | |
| with gr.Column(scale=1): | |
| gr.HTML(""" | |
| <div class="feature-box"> | |
| <h3>🔊 Step 3: Audio Generation</h3> | |
| <p>Text is converted to natural-sounding speech using Supertonic TTS.</p> | |
| </div> | |
| """) | |
| # Main Workflow Section | |
| with gr.Row(): | |
| # Left Column - Input | |
| with gr.Column(scale=1, elem_classes="upload-section"): | |
| gr.Markdown("### 📤 Upload Your Image", elem_classes="section-title") | |
| image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| gr.Markdown("### 🎚️ Voice Settings", elem_classes="section-title") | |
| voice_dropdown = gr.Dropdown( | |
| choices=[opt[0] for opt in VOICE_OPTIONS], | |
| label="Select Voice Style", | |
| value="M5 - Male Voice (Default)", | |
| info="Choose a voice style for the generated audio" | |
| ) | |
| generate_btn = gr.Button( | |
| "✨ Generate Audio", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| # Right Column - Output | |
| with gr.Column(scale=1, elem_classes="output-section"): | |
| gr.Markdown("### 📝 Extracted Text", elem_classes="section-title") | |
| text_output = gr.Textbox( | |
| label="", | |
| lines=6, | |
| show_label=False, | |
| placeholder="The extracted text will appear here...", | |
| interactive=False | |
| ) | |
| gr.Markdown("### 🔊 Generated Audio", elem_classes="section-title") | |
| audio_output = gr.Audio( | |
| label="", | |
| type="filepath", | |
| show_label=False | |
| ) | |
| # Connection | |
| generate_btn.click( | |
| fn=image_to_voice, | |
| inputs=[image_input, voice_dropdown], | |
| outputs=[audio_output, text_output], | |
| show_progress="full" | |
| ) | |
| # ===== TAB 2: Mood Chart ===== | |
| with gr.TabItem("😊 Mood Chart"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📤 Upload Your Image", elem_classes="section-title") | |
| mood_image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| mood_analyze_btn = gr.Button( | |
| "🔍 Analyze Mood", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📊 Mood Analysis Results", elem_classes="section-title") | |
| mood_output = gr.Textbox( | |
| label="", | |
| lines=10, | |
| show_label=False, | |
| placeholder="Mood analysis will appear here...", | |
| interactive=False | |
| ) | |
| mood_analyze_btn.click( | |
| fn=analyze_mood_from_image, | |
| inputs=[mood_image_input], | |
| outputs=[mood_output], | |
| show_progress="full" | |
| ) | |
| # ===== TAB 3: Story Generation ===== | |
| with gr.TabItem("📖 AI Story Generator"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📤 Upload Your Image", elem_classes="section-title") | |
| story_image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| gr.Markdown("### 🎭 Story Theme", elem_classes="section-title") | |
| story_theme_dropdown = gr.Dropdown( | |
| choices=[ | |
| "Adventure", | |
| "Fantasy", | |
| "Mystery", | |
| "Romance", | |
| "Science Fiction", | |
| "Comedy", | |
| "Educational", | |
| "Inspirational" | |
| ], | |
| label="Select Story Theme", | |
| value="Adventure", | |
| info="Choose a theme for your story" | |
| ) | |
| story_generate_btn = gr.Button( | |
| "✍️ Generate Story", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📚 Generated Story", elem_classes="section-title") | |
| story_output = gr.Textbox( | |
| label="", | |
| lines=12, | |
| show_label=False, | |
| placeholder="Your story will appear here...", | |
| interactive=False | |
| ) | |
| story_generate_btn.click( | |
| fn=ai_story_generation, | |
| inputs=[story_image_input, story_theme_dropdown], | |
| outputs=[story_output], | |
| show_progress="full" | |
| ) | |
| # ===== TAB 3B: Hugging Face Picture to Story ===== | |
| with gr.TabItem("🎨 HuggingFace Picture to Story"): | |
| gr.Markdown(""" | |
| ### 🤖 Advanced AI Story Generation using Hugging Face | |
| This feature uses the cutting-edge **Vision Transformer (ViT) + GPT-2** model from Hugging Face | |
| to directly transform your picture into a creative narrative story. | |
| """) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📤 Upload Your Picture", elem_classes="section-title") | |
| hf_story_image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| hf_story_generate_btn = gr.Button( | |
| "🚀 Transform to Story", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📖 AI-Generated Story", elem_classes="section-title") | |
| hf_story_output = gr.Textbox( | |
| label="", | |
| lines=14, | |
| show_label=False, | |
| placeholder="Your AI story will appear here...", | |
| interactive=False | |
| ) | |
| hf_story_generate_btn.click( | |
| fn=huggingface_picture_to_story, | |
| inputs=[hf_story_image_input], | |
| outputs=[hf_story_output], | |
| show_progress="full" | |
| ) | |
| # ===== TAB 4: Study Helper ===== | |
| with gr.TabItem("📚 AI Study Helper"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📤 Upload Your Study Material", elem_classes="section-title") | |
| study_image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| gr.Markdown("### 🎯 Study Assistance Type", elem_classes="section-title") | |
| study_type_dropdown = gr.Dropdown( | |
| choices=[ | |
| "Summary", | |
| "Quiz Questions", | |
| "Learning Tips", | |
| "Note-Taking" | |
| ], | |
| label="Select Study Aid", | |
| value="Summary", | |
| info="Choose the type of study assistance you need" | |
| ) | |
| study_generate_btn = gr.Button( | |
| "🚀 Generate Study Aid", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📖 Study Insights", elem_classes="section-title") | |
| study_output = gr.Textbox( | |
| label="", | |
| lines=12, | |
| show_label=False, | |
| placeholder="Study insights will appear here...", | |
| interactive=False | |
| ) | |
| study_generate_btn.click( | |
| fn=ai_study_helper, | |
| inputs=[study_image_input, study_type_dropdown], | |
| outputs=[study_output], | |
| show_progress="full" | |
| ) | |
| # ===== TAB 5: Study Helper for Kids ===== | |
| with gr.TabItem("🎨 Study Helper for Kids"): | |
| gr.Markdown(""" | |
| # 🌟 **WELCOME TO AWESOME LEARNING LAND!** 🌟 | |
| 📚 **Learning is FUN and EXCITING!** | |
| Upload your homework, and let our super cool AI help you learn in amazing ways! | |
| Choose your favorite learning style and get ready to become a LEARNING SUPERSTAR! 🚀 | |
| """) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📤 Upload Your Homework", elem_classes="section-title") | |
| kids_study_image_input = gr.Image( | |
| label="", | |
| type="pil", | |
| height=350, | |
| show_label=False | |
| ) | |
| gr.Markdown("### 🎮 Pick Your Learning Style", elem_classes="section-title") | |
| kids_learning_style_dropdown = gr.Dropdown( | |
| choices=[ | |
| "Fun Summary", | |
| "Interactive Quiz", | |
| "Memory Game", | |
| "Learning Tips for Kids" | |
| ], | |
| label="What sounds fun to you?", | |
| value="Fun Summary", | |
| info="Choose how you want to learn! 🎯" | |
| ) | |
| kids_study_generate_btn = gr.Button( | |
| "🎉 Start Learning Adventure!", | |
| variant="primary", | |
| elem_classes="generate-btn", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 🌈 Your Learning Experience", elem_classes="section-title") | |
| kids_study_output = gr.Textbox( | |
| label="", | |
| lines=14, | |
| show_label=False, | |
| placeholder="Your fun learning content will appear here! Get ready for an adventure! 🚀", | |
| interactive=False | |
| ) | |
| kids_study_generate_btn.click( | |
| fn=ai_study_helper_for_kids, | |
| inputs=[kids_study_image_input, kids_learning_style_dropdown], | |
| outputs=[kids_study_output], | |
| show_progress="full" | |
| ) | |
| gr.HTML(""" | |
| <div class="footer"> | |
| <p>Powered by <strong>Hugging Face Transformers</strong> & <strong>Supertonic TTS</strong> | | |
| Built with ❤️ using Gradio</p> | |
| </div> | |
| """) | |
| if __name__ == "__main__": | |
| demo.launch() | |