Update main.py

main.py

@@ -50,46 +50,73 @@ async def detect(file: UploadFile = File(...)):
     contents = await file.read()
     filename = file.filename.lower()
 
-    # لو فيديو
+    # ── فيديو ──
     if any(filename.endswith(ext) for ext in ['.mp4', '.avi', '.mov', '.mkv']):
         with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as tmp:
             tmp.write(contents)
             tmp_path = tmp.name
 
-        cap = cv2.VideoCapture(tmp_path)
-        ret, frame = cap.read()
+        cap          = cv2.VideoCapture(tmp_path)
+        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+
+        # نحلل 5 frames موزعة على الفيديو
+        sample_points  = [int(total_frames * i / 5) for i in range(1, 6)]
+        all_detections = []
+
+        for frame_num in sample_points:
+            cap.set(cv2.CAP_PROP_POS_FRAMES, frame_num)
+            ret, frame = cap.read()
+            if not ret:
+                continue
+
+            img     = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+            results = model(img)
+
+            for box in results[0].boxes:
+                cls   = int(box.cls)
+                conf  = float(box.conf)
+                xywhn = box.xywhn[0].tolist()
+                area  = xywhn[2] * xywhn[3]
+                all_detections.append({
+                    "damage_type": CLASS_NAMES.get(cls, 'other'),
+                    "confidence" : round(conf, 3),
+                    "severity"   : get_severity(conf, area),
+                    "bbox"       : xywhn,
+                    "frame"      : frame_num
+                })
+
         cap.release()
         os.unlink(tmp_path)
 
-        if not ret:
-            return {"error": "cannot read video", "total": 0, "detections": []}
-
-        img = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+        return {
+            "total"     : len(all_detections),
+            "detections": all_detections
+        }
 
-    # لو صورة
+    # ── صورة ──
     else:
         try:
             img = Image.open(io.BytesIO(contents))
         except Exception as e:
             return {"error": str(e), "total": 0, "detections": []}
 
-    results     = model(img)
-    detections  = []
-
-    for box in results[0].boxes:
-        cls    = int(box.cls)
-        conf   = float(box.conf)
-        xywhn  = box.xywhn[0].tolist()
-        area   = xywhn[2] * xywhn[3]
-
-        detections.append({
-            "damage_type": CLASS_NAMES.get(cls, 'other'),
-            "confidence" : round(conf, 3),
-            "severity"   : get_severity(conf, area),
-            "bbox"       : xywhn
-        })
-
-    return {
-        "total"     : len(detections),
-        "detections": detections
-    }
+        results        = model(img)
+        all_detections = []
+
+        for box in results[0].boxes:
+            cls   = int(box.cls)
+            conf  = float(box.conf)
+            xywhn = box.xywhn[0].tolist()
+            area  = xywhn[2] * xywhn[3]
+            all_detections.append({
+                "damage_type": CLASS_NAMES.get(cls, 'other'),
+                "confidence" : round(conf, 3),
+                "severity"   : get_severity(conf, area),
+                "bbox"       : xywhn,
+                "frame"      : 0
+            })
+
+        return {
+            "total"     : len(all_detections),
+            "detections": all_detections
+        }