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Hashii1729 commited on Jun 24

Commit

d7e6224

1 Parent(s): 2805777

Refactor analysis endpoints: remove deprecated response models, enhance JSON output formatting, and improve object detection functionality

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Files changed (1) hide show

fast.py +59 -54

fast.py CHANGED Viewed

@@ -1741,9 +1741,6 @@ class StructuredAnalysisResponse(BaseModel):
     confidence_score: float
     detected_items: List[Dict[str, Any]] = []
-class AnalysisResponse(BaseModel):
-    analysis: str
 class DetailedAnalysisResponse(BaseModel):
     structured_analysis: StructuredAnalysisResponse
     raw_analysis: str
@@ -1766,15 +1763,15 @@ async def root():
         </style>
     </head>
     <body>
-        <h1>🎽 Fashion Analyzer</h1>
-        <p>Upload an image of clothing to get detailed fashion analysis</p>
         <div class="upload-area">
             <input type="file" id="imageInput" accept="image/*" style="margin: 10px;">
             <br>
-            <button onclick="analyzeImage()" style="padding: 10px 20px; margin: 10px;">Analyze Fashion (Detailed)</button>
-            <button onclick="analyzeStructured()" style="padding: 10px 20px; margin: 10px;">Analyze Fashion (Structured)</button>
-            <button onclick="analyzeJSON()" style="padding: 10px 20px; margin: 10px; background-color: #28a745; color: white;">Analyze Fashion (JSON)</button>
             <button onclick="checkDeepFashion2Status()" style="padding: 10px 20px; margin: 10px; background-color: #6f42c1; color: white;">DeepFashion2 Status</button>
             <br>
             <a href="/refined-prompt" target="_blank" style="color: #007bff; text-decoration: none;">View Refined Prompt Format</a>
@@ -1798,7 +1795,7 @@ async def root():
             const formData = new FormData();
             formData.append('file', file);
-            document.getElementById('analysisText').textContent = 'Analyzing... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
@@ -1808,7 +1805,20 @@ async def root():
                 });
                 const result = await response.json();
-                document.getElementById('analysisText').textContent = result.analysis;
             } catch (error) {
                 document.getElementById('analysisText').textContent = 'Error: ' + error.message;
             }
@@ -1826,7 +1836,7 @@ async def root():
             const formData = new FormData();
             formData.append('file', file);
-            document.getElementById('analysisText').textContent = 'Analyzing with structured format... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
@@ -1836,13 +1846,18 @@ async def root():
                 });
                 const result = await response.json();
-                document.getElementById('analysisText').textContent = result.analysis;
             } catch (error) {
                 document.getElementById('analysisText').textContent = 'Error: ' + error.message;
             }
         }
-        async function analyzeJSON() {
             const input = document.getElementById('imageInput');
             const file = input.files[0];
@@ -1854,11 +1869,11 @@ async def root():
             const formData = new FormData();
             formData.append('file', file);
-            document.getElementById('analysisText').textContent = 'Analyzing with JSON format... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
-                const response = await fetch('/analyze-json', {
                     method: 'POST',
                     body: formData
                 });
@@ -1866,14 +1881,8 @@ async def root():
                 const result = await response.json();
                 // Format JSON output nicely
-                let jsonOutput = 'JSON FASHION ANALYSIS RESULT:\\n\\n';
-                jsonOutput += 'STRUCTURED ANALYSIS:\\n';
-                jsonOutput += JSON.stringify(result.structured_analysis, null, 2);
-                jsonOutput += '\\n\\nPROCESSING INFO:\\n';
-                jsonOutput += `Processing Time: ${result.processing_time.toFixed(3)} seconds\\n`;
-                jsonOutput += `Device: ${result.model_info.device}\\n`;
-                jsonOutput += `Detection Model: ${result.model_info.detection_model}\\n`;
-                jsonOutput += `Feature Model: ${result.model_info.feature_model}\\n`;
                 document.getElementById('analysisText').textContent = jsonOutput;
             } catch (error) {
@@ -1956,38 +1965,8 @@ async def root():
     </html>
     """
-@app.post("/analyze-image", response_model=AnalysisResponse)
 async def analyze_image(file: UploadFile = File(...)):
-    """Analyze uploaded image"""
-    try:
-        # Read image bytes
-        image_bytes = await file.read()
-        # Analyze the clothing
-        analysis = analyzer.analyze_clothing_from_bytes(image_bytes)
-        return AnalysisResponse(analysis=analysis)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error analyzing image: {str(e)}")
-@app.post("/analyze-structured", response_model=AnalysisResponse)
-async def analyze_structured(file: UploadFile = File(...)):
-    """Analyze uploaded image with structured format"""
-    try:
-        # Read image bytes
-        image_bytes = await file.read()
-        # Get structured analysis
-        analysis = analyzer.analyze_clothing_structured_format(image_bytes)
-        return AnalysisResponse(analysis=analysis)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error analyzing image: {str(e)}")
-@app.post("/analyze-json", response_model=DetailedAnalysisResponse)
-async def analyze_json(file: UploadFile = File(...)):
     """Analyze uploaded image and return structured JSON response"""
     try:
         start_time = time.time()
@@ -2026,6 +2005,32 @@ async def analyze_json(file: UploadFile = File(...)):
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error analyzing image: {str(e)}")
 @app.post("/detect-objects", response_model=Dict[str, Any])
 async def detect_objects(file: UploadFile = File(...)):
     """Detect fashion objects and return JSON structure"""

     confidence_score: float
     detected_items: List[Dict[str, Any]] = []
 class DetailedAnalysisResponse(BaseModel):
     structured_analysis: StructuredAnalysisResponse
     raw_analysis: str
         </style>
     </head>
     <body>
+        <h1>🎽 Fashion Analyzer - JSON API</h1>
+        <p>Upload an image of clothing to get detailed fashion analysis in structured JSON format</p>
         <div class="upload-area">
             <input type="file" id="imageInput" accept="image/*" style="margin: 10px;">
             <br>
+            <button onclick="analyzeImage()" style="padding: 10px 20px; margin: 10px; background-color: #28a745; color: white;">Analyze Fashion (Detailed JSON)</button>
+            <button onclick="analyzeStructured()" style="padding: 10px 20px; margin: 10px; background-color: #007bff; color: white;">Analyze Fashion (Structured JSON)</button>
+            <button onclick="detectObjects()" style="padding: 10px 20px; margin: 10px; background-color: #fd7e14; color: white;">Detect Objects Only</button>
             <button onclick="checkDeepFashion2Status()" style="padding: 10px 20px; margin: 10px; background-color: #6f42c1; color: white;">DeepFashion2 Status</button>
             <br>
             <a href="/refined-prompt" target="_blank" style="color: #007bff; text-decoration: none;">View Refined Prompt Format</a>
             const formData = new FormData();
             formData.append('file', file);
+            document.getElementById('analysisText').textContent = 'Analyzing with detailed JSON format... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
                 });
                 const result = await response.json();
+                // Format JSON output nicely
+                let jsonOutput = 'DETAILED FASHION ANALYSIS RESULT:\\n\\n';
+                jsonOutput += 'STRUCTURED ANALYSIS:\\n';
+                jsonOutput += JSON.stringify(result.structured_analysis, null, 2);
+                jsonOutput += '\\n\\nRAW ANALYSIS:\\n';
+                jsonOutput += result.raw_analysis;
+                jsonOutput += '\\n\\nPROCESSING INFO:\\n';
+                jsonOutput += `Processing Time: ${result.processing_time.toFixed(3)} seconds\\n`;
+                jsonOutput += `Device: ${result.model_info.device}\\n`;
+                jsonOutput += `Detection Model: ${result.model_info.detection_model}\\n`;
+                jsonOutput += `Feature Model: ${result.model_info.feature_model}\\n`;
+                document.getElementById('analysisText').textContent = jsonOutput;
             } catch (error) {
                 document.getElementById('analysisText').textContent = 'Error: ' + error.message;
             }
             const formData = new FormData();
             formData.append('file', file);
+            document.getElementById('analysisText').textContent = 'Analyzing with structured JSON format... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
                 });
                 const result = await response.json();
+                // Format JSON output nicely
+                let jsonOutput = 'STRUCTURED FASHION ANALYSIS RESULT:\\n\\n';
+                jsonOutput += JSON.stringify(result, null, 2);
+                document.getElementById('analysisText').textContent = jsonOutput;
             } catch (error) {
                 document.getElementById('analysisText').textContent = 'Error: ' + error.message;
             }
         }
+        async function detectObjects() {
             const input = document.getElementById('imageInput');
             const file = input.files[0];
             const formData = new FormData();
             formData.append('file', file);
+            document.getElementById('analysisText').textContent = 'Detecting fashion objects... Please wait...';
             document.getElementById('result').style.display = 'block';
             try {
+                const response = await fetch('/detect-objects', {
                     method: 'POST',
                     body: formData
                 });
                 const result = await response.json();
                 // Format JSON output nicely
+                let jsonOutput = 'FASHION OBJECT DETECTION RESULT:\\n\\n';
+                jsonOutput += JSON.stringify(result, null, 2);
                 document.getElementById('analysisText').textContent = jsonOutput;
             } catch (error) {
     </html>
     """
+@app.post("/analyze-image", response_model=DetailedAnalysisResponse)
 async def analyze_image(file: UploadFile = File(...)):
     """Analyze uploaded image and return structured JSON response"""
     try:
         start_time = time.time()
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error analyzing image: {str(e)}")
+@app.post("/analyze-structured", response_model=StructuredAnalysisResponse)
+async def analyze_structured(file: UploadFile = File(...)):
+    """Analyze uploaded image with structured format and return JSON"""
+    try:
+        # Read image bytes
+        image_bytes = await file.read()
+        # Process image
+        image = analyzer.process_image_from_bytes(image_bytes)
+        # Get fashion object detection results
+        detection_results = analyzer.detect_fashion_objects(image)
+        # Get basic image description
+        basic_description = analyzer.get_basic_description(image)
+        # Extract structured information
+        structured_analysis = analyzer.parse_structured_analysis(detection_results, basic_description)
+        return structured_analysis
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error analyzing image: {str(e)}")
 @app.post("/detect-objects", response_model=Dict[str, Any])
 async def detect_objects(file: UploadFile = File(...)):
     """Detect fashion objects and return JSON structure"""