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Dockerfile

@@ -1,51 +1,51 @@
-FROM python:3.9-slim
-
-# Set working directory
-WORKDIR /app
-
-# Install system dependencies
-RUN apt-get update && apt-get install -y \
-    git \
-    wget \
-    curl \
-    build-essential \
-    libgl1-mesa-dev \
-    libglib2.0-0 \
-    libsm6 \
-    libxext6 \
-    libxrender-dev \
-    libgomp1 \
-    libgcc-s1 \
-    python3-opencv \
-    ffmpeg \
-    libsm6 \
-    libxext6 \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy requirements first to leverage Docker cache
-COPY requirements.txt .
-
-# Install Python dependencies
-RUN pip install --no-cache-dir --upgrade pip && \
-    pip install --no-cache-dir -r requirements.txt
-
-# Copy application code
-COPY . .
-
-# Create necessary directories
-RUN mkdir -p static/css templates
-
-# Set environment variables for Hugging Face Spaces
-ENV PYTHONPATH=/app
-ENV FLASK_APP=app.py
-ENV FLASK_ENV=production
-
-# Expose port for Hugging Face Spaces
-EXPOSE 7860
-
-# Health check
-HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
-    CMD curl -f http://localhost:7860/health || exit 1
-
-# Command to run the application
+FROM python:3.9-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    wget \
+    curl \
+    build-essential \
+    libgl1-mesa-dev \
+    libglib2.0-0 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    libgomp1 \
+    libgcc-s1 \
+    ffmpeg \
+    libgtk-3-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
+
+# Install Python dependencies with specific order
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir numpy==1.21.6 && \
+    pip install --no-cache-dir opencv-python-headless==4.8.1.78 && \
+    pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create necessary directories
+RUN mkdir -p static/css templates
+
+# Set environment variables for Hugging Face Spaces
+ENV PYTHONPATH=/app
+ENV FLASK_APP=app.py
+ENV FLASK_ENV=production
+
+# Expose port for Hugging Face Spaces
+EXPOSE 7860
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:7860/health || exit 1
+
+# Command to run the application
 CMD ["python", "app.py"]

app.py

@@ -4,11 +4,17 @@ import torch
 from flask import Flask, render_template, request, jsonify, url_for
 from PIL import Image
 import base64
-from transformers import AutoTokenizer
 import logging
 
-# Import model từ file hiện tại
-from blip2_vicuna_instruct import Blip2VicunaInstruct
+# Safe import with error handling
+try:
+    from transformers import AutoTokenizer
+    from blip2_vicuna_instruct import Blip2VicunaInstruct
+    MODEL_AVAILABLE = True
+except ImportError as e:
+    logging.error(f"Model import failed: {e}")
+    MODEL_AVAILABLE = False
+    Blip2VicunaInstruct = None
 
 app = Flask(__name__)
 app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
@@ -21,6 +27,10 @@ def load_model():
     """Load BLIP2 Vicuna model"""
     global model, device
     
+    if not MODEL_AVAILABLE:
+        logging.error("Model is not available due to import errors")
+        return
+    
     try:
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         logging.info(f"Using device: {device}")
@@ -119,6 +129,9 @@ def index():
 def predict():
     """Handle image upload and prediction"""
     try:
+        if not MODEL_AVAILABLE:
+            return jsonify({'error': 'Model is not available due to import errors. Please check dependencies.'}), 500
+            
         if 'image' not in request.files:
             return jsonify({'error': 'No image file provided'}), 400
         
@@ -129,22 +142,26 @@ def predict():
         # Đọc và xử lý image
         image = Image.open(io.BytesIO(file.read()))
         
-        # Preprocess image
-        image_tensor = preprocess_image(image)
-        if image_tensor is None:
-            return jsonify({'error': 'Failed to process image'}), 400
-        
         # Get custom prompt if provided
         custom_prompt = request.form.get('prompt', 'What emotion is shown in this image?')
         
-        # Predict emotion
-        emotion_result = predict_emotion(image_tensor, custom_prompt)
-        
         # Convert image to base64 for display
         buffered = io.BytesIO()
         image.save(buffered, format="PNG")
         img_str = base64.b64encode(buffered.getvalue()).decode()
         
+        # If model is not loaded, return a fallback response
+        if model is None:
+            emotion_result = "Model not loaded - unable to analyze emotion. This might be due to missing model weights or configuration issues."
+        else:
+            # Preprocess image
+            image_tensor = preprocess_image(image)
+            if image_tensor is None:
+                return jsonify({'error': 'Failed to process image'}), 400
+            
+            # Predict emotion
+            emotion_result = predict_emotion(image_tensor, custom_prompt)
+        
         return jsonify({
             'success': True,
             'emotion': emotion_result,
@@ -161,6 +178,7 @@ def health():
     """Health check endpoint"""
     return jsonify({
         'status': 'healthy',
+        'model_available': MODEL_AVAILABLE,
         'model_loaded': model is not None,
         'device': str(device) if device else 'unknown'
     })

requirements.txt

@@ -2,21 +2,21 @@
 Flask==2.3.3
 gunicorn==21.2.0
 
-# Core ML Libraries
+# Core ML Libraries  
 torch>=1.10.0
 torchvision>=0.11.0
 transformers>=4.28.0
 pillow>=10.0.0
 
-# Image Processing
-opencv-python-headless>=4.5.0
+# Image Processing (pinned versions for compatibility)
+numpy==1.21.6
+opencv-python-headless==4.8.1.78
 
 # LAVIS dependencies (for BLIP2)
 salesforce-lavis
 omegaconf>=2.3.0
 
 # Data handling
-numpy>=1.24.0
 pandas>=2.0.0
 
 # Other utilities

test_deps.py

@@ -0,0 +1,79 @@
+#!/usr/bin/env python3
+"""
+Test script để kiểm tra dependencies và model loading
+"""
+
+import sys
+import importlib
+
+def test_dependencies():
+    """Test các dependencies cơ bản"""
+    required_packages = [
+        'flask',
+        'torch',
+        'torchvision', 
+        'transformers',
+        'PIL',
+        'numpy',
+        'cv2'
+    ]
+    
+    results = {}
+    
+    for package in required_packages:
+        try:
+            if package == 'PIL':
+                importlib.import_module('PIL')
+            elif package == 'cv2':
+                importlib.import_module('cv2')
+            else:
+                importlib.import_module(package)
+            results[package] = "✅ OK"
+        except ImportError as e:
+            results[package] = f"❌ FAILED: {e}"
+    
+    return results
+
+def test_model_import():
+    """Test import model"""
+    try:
+        from blip2_vicuna_instruct import Blip2VicunaInstruct
+        return "✅ Model import successful"
+    except ImportError as e:
+        return f"❌ Model import failed: {e}"
+
+def test_basic_functionality():
+    """Test basic Flask app functionality"""
+    try:
+        from flask import Flask
+        app = Flask(__name__)
+        return "✅ Flask app creation successful"
+    except Exception as e:
+        return f"❌ Flask app creation failed: {e}"
+
+if __name__ == "__main__":
+    print("🔍 Testing EmoVIT Dependencies...")
+    print("=" * 50)
+    
+    # Test dependencies
+    print("\n📦 Dependency Check:")
+    deps = test_dependencies()
+    for package, status in deps.items():
+        print(f"  {package}: {status}")
+    
+    # Test model import
+    print(f"\n🤖 Model Import: {test_model_import()}")
+    
+    # Test Flask
+    print(f"\n🌐 Flask Test: {test_basic_functionality()}")
+    
+    # Summary
+    failed_deps = [pkg for pkg, status in deps.items() if "❌" in status]
+    
+    if failed_deps:
+        print(f"\n❌ Issues found with: {', '.join(failed_deps)}")
+        print("Please check the requirements.txt and Dockerfile")
+        sys.exit(1)
+    else:
+        print("\n✅ All basic dependencies OK!")
+        print("You can try running: python app.py")