Update app.py

app.py

@@ -1,59 +1,280 @@
+import os
 from flask import Flask, request, jsonify
-from concurrent.futures import ThreadPoolExecutor
+from werkzeug.utils import secure_filename
+import uuid
+from pathlib import Path
 
-from skin_analysis import (
-    get_hydration_factors, compute_hydration_score,
-    get_pigmentation_factors, compute_pigmentation_score,
-    get_acne_factors, compute_acne_score,
-    get_fitzpatrick_type, get_eye_age, get_skin_age
+from skin_analysis_optimized_v2 import (
+    get_comprehensive_analysis,
+    get_pores_breakdown,
+    get_wrinkle_breakdown,
+    get_usage_stats,
+    clear_cache
 )
 
 app = Flask(__name__)
 
-executor = ThreadPoolExecutor(max_workers=6)
+# Configuration
+UPLOAD_FOLDER = "temp_uploads"
+ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'webp'}
+MAX_FILE_SIZE = 10 * 1024 * 1024  # 10MB
+
+# Create upload folder if it doesn't exist
+Path(UPLOAD_FOLDER).mkdir(parents=True, exist_ok=True)
+
+def allowed_file(filename):
+    """Check if file extension is allowed"""
+    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+def cleanup_temp_file(filepath):
+    """Delete temporary file"""
+    try:
+        if os.path.exists(filepath):
+            os.remove(filepath)
+    except Exception as e:
+        print(f"Warning: Could not delete temp file {filepath}: {e}")
 
 @app.route("/")
 def home():
-    return {"status": "Skin Analysis API Running"}
+    """Health check endpoint"""
+    return jsonify({
+        "status": "Skin Analysis API Running",
+        "version": "2.0",
+        "features": [
+            "hydration",
+            "pigmentation",
+            "acne",
+            "pores",
+            "wrinkles",
+            "age_analysis"
+        ],
+        "endpoints": {
+            "analyze": "/analyze (POST)",
+            "analyze_detailed": "/analyze/detailed (POST)",
+            "stats": "/stats (GET)",
+            "clear_cache": "/cache/clear (POST)"
+        }
+    })
 
 @app.route("/analyze", methods=["POST"])
 def analyze():
+    """
+    Main analysis endpoint - returns scores and basic data
+    """
+    # Validate request
     if "image" not in request.files:
         return jsonify({"error": "No image uploaded"}), 400
+    
+    img = request.files["image"]
+    
+    if img.filename == '':
+        return jsonify({"error": "No image selected"}), 400
+    
+    if not allowed_file(img.filename):
+        return jsonify({
+            "error": f"Invalid file type. Allowed types: {', '.join(ALLOWED_EXTENSIONS)}"
+        }), 400
+    
+    # Check file size
+    img.seek(0, os.SEEK_END)
+    file_size = img.tell()
+    img.seek(0)
+    
+    if file_size > MAX_FILE_SIZE:
+        return jsonify({
+            "error": f"File too large. Maximum size: {MAX_FILE_SIZE / (1024*1024):.1f}MB"
+        }), 400
+    
+    # Save image with unique filename
+    filename = secure_filename(img.filename)
+    unique_filename = f"{uuid.uuid4()}_{filename}"
+    temp_path = os.path.join(UPLOAD_FOLDER, unique_filename)
+    
+    try:
+        img.save(temp_path)
+        
+        # Perform comprehensive analysis (single API call)
+        analysis = get_comprehensive_analysis(temp_path)
+        
+        if not analysis:
+            return jsonify({
+                "error": "Analysis failed. Please try again or contact support."
+            }), 500
+        
+        # Build response
+        result = {
+            "success": True,
+            "scores": {
+                "hydration": analysis['scores']['hydration'],
+                "pigmentation": 100 - analysis['scores']['pigmentation'],  # Invert (higher = better)
+                "acne": 100 - analysis['scores']['acne'],  # Invert (higher = better)
+                "pores": 100 - analysis['scores']['pores'],  # Invert (higher = better)
+                "wrinkles": 100 - analysis['scores']['wrinkles']  # Invert (higher = better)
+            },
+            "raw_factors": {
+                "hydration": analysis['raw_data']['hydration'],
+                "pigmentation": analysis['raw_data']['pigmentation'],
+                "acne": analysis['raw_data']['acne'],
+                "pores": analysis['raw_data']['pores'],
+                "wrinkles": analysis['raw_data']['wrinkles']
+            },
+            "age_analysis": {
+                "fitzpatrick_type": analysis['age_analysis']['fitzpatrick_type'],
+                "eye_age": analysis['age_analysis']['eye_age'],
+                "skin_age": analysis['age_analysis']['skin_age']
+            },
+            "metadata": analysis['metadata']
+        }
+        
+        return jsonify(result)
+    
+    except Exception as e:
+        return jsonify({
+            "error": f"Server error: {str(e)}"
+        }), 500
+    
+    finally:
+        # Cleanup temp file
+        cleanup_temp_file(temp_path)
 
+@app.route("/analyze/detailed", methods=["POST"])
+def analyze_detailed():
+    """
+    Detailed analysis endpoint - includes breakdowns for pores and wrinkles
+    """
+    # Validate request
+    if "image" not in request.files:
+        return jsonify({"error": "No image uploaded"}), 400
+    
     img = request.files["image"]
-    img.save("temp.jpg")
-
-    # Launch all 6 tasks in parallel
-    hydration_f = executor.submit(get_hydration_factors, "temp.jpg")
-    pigmentation_f = executor.submit(get_pigmentation_factors, "temp.jpg")
-    acne_f = executor.submit(get_acne_factors, "temp.jpg")
-    fitz_f = executor.submit(get_fitzpatrick_type, "temp.jpg")
-    eye_f = executor.submit(get_eye_age, "temp.jpg")
-    skin_f = executor.submit(get_skin_age, "temp.jpg")
-
-    hydration = hydration_f.result()
-    pigmentation = pigmentation_f.result()
-    acne = acne_f.result()
-    fitz_type = fitz_f.result()
-    eye_age = eye_f.result()
-    skin_age = skin_f.result()
-
-    result = {
-        "hydration_score": compute_hydration_score(hydration),
-        "pigmentation_score": 100 - compute_pigmentation_score(pigmentation),
-        "acne_score": 100 - compute_acne_score(acne),
-
-        "hydration_factors": hydration,
-        "pigmentation_factors": pigmentation,
-        "acne_factors": acne,
-
-        "fitzpatrick_type": fitz_type,
-        "eye_age": eye_age,
-        "skin_age": skin_age
-    }
-
-    return jsonify(result)
+    
+    if img.filename == '':
+        return jsonify({"error": "No image selected"}), 400
+    
+    if not allowed_file(img.filename):
+        return jsonify({
+            "error": f"Invalid file type. Allowed types: {', '.join(ALLOWED_EXTENSIONS)}"
+        }), 400
+    
+    # Save image
+    filename = secure_filename(img.filename)
+    unique_filename = f"{uuid.uuid4()}_{filename}"
+    temp_path = os.path.join(UPLOAD_FOLDER, unique_filename)
+    
+    try:
+        img.save(temp_path)
+        
+        # Perform comprehensive analysis
+        analysis = get_comprehensive_analysis(temp_path)
+        
+        if not analysis:
+            return jsonify({
+                "error": "Analysis failed. Please try again."
+            }), 500
+        
+        # Get detailed breakdowns
+        pores_detail = get_pores_breakdown(temp_path)
+        wrinkles_detail = get_wrinkle_breakdown(temp_path)
+        
+        # Build detailed response
+        result = {
+            "success": True,
+            "scores": {
+                "hydration": analysis['scores']['hydration'],
+                "pigmentation": 100 - analysis['scores']['pigmentation'],
+                "acne": 100 - analysis['scores']['acne'],
+                "pores": 100 - analysis['scores']['pores'],
+                "wrinkles": 100 - analysis['scores']['wrinkles']
+            },
+            "raw_factors": {
+                "hydration": analysis['raw_data']['hydration'],
+                "pigmentation": analysis['raw_data']['pigmentation'],
+                "acne": analysis['raw_data']['acne'],
+                "pores": analysis['raw_data']['pores'],
+                "wrinkles": analysis['raw_data']['wrinkles']
+            },
+            "age_analysis": analysis['age_analysis'],
+            "detailed_analysis": {
+                "pores": pores_detail,
+                "wrinkles": wrinkles_detail
+            },
+            "metadata": analysis['metadata']
+        }
+        
+        return jsonify(result)
+    
+    except Exception as e:
+        return jsonify({
+            "error": f"Server error: {str(e)}"
+        }), 500
+    
+    finally:
+        cleanup_temp_file(temp_path)
+
+@app.route("/stats", methods=["GET"])
+def stats():
+    """
+    Get API usage statistics
+    """
+    try:
+        usage_stats = get_usage_stats()
+        return jsonify({
+            "success": True,
+            "usage": usage_stats
+        })
+    except Exception as e:
+        return jsonify({
+            "error": f"Could not retrieve stats: {str(e)}"
+        }), 500
+
+@app.route("/cache/clear", methods=["POST"])
+def clear_analysis_cache():
+    """
+    Clear the analysis cache (admin endpoint)
+    """
+    try:
+        clear_cache()
+        return jsonify({
+            "success": True,
+            "message": "Cache cleared successfully"
+        })
+    except Exception as e:
+        return jsonify({
+            "error": f"Could not clear cache: {str(e)}"
+        }), 500
+
+@app.route("/health", methods=["GET"])
+def health_check():
+    """
+    Health check endpoint for monitoring
+    """
+    return jsonify({
+        "status": "healthy",
+        "service": "Skin Analysis API",
+        "version": "2.0"
+    })
+
+@app.errorhandler(413)
+def request_entity_too_large(error):
+    """Handle file too large error"""
+    return jsonify({
+        "error": f"File too large. Maximum size: {MAX_FILE_SIZE / (1024*1024):.1f}MB"
+    }), 413
+
+@app.errorhandler(500)
+def internal_server_error(error):
+    """Handle internal server errors"""
+    return jsonify({
+        "error": "Internal server error. Please try again later."
+    }), 500
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+    # For production, use a proper WSGI server like gunicorn
+    # gunicorn -w 4 -b 0.0.0.0:7860 app:app
+    
+    # Development server
+    app.run(
+        host="0.0.0.0",
+        port=7860,
+        debug=False  # Set to False in production
+    )