conf fixed

api/utils.py

@@ -86,7 +86,7 @@ def extract_metadata(image_bytes):
 def process_image(image):
     """Run 3-stage detection and classification with dynamic confidence"""
     detections = []
-    results = DETECT_MODEL(image,conf=0.8 ,iou=0.7,agnostic_nms=True)  # Stage 1: Deer detection
+    results = DETECT_MODEL(image,conf=0.8 ,iou=0.4,agnostic_nms=True)  # Stage 1: Deer detection
     for r in results:
         for box in r.boxes:
             x1, y1, x2, y2 = map(int, box.xyxy[0])
@@ -94,7 +94,7 @@ def process_image(image):
             if crop.size == 0:
                 continue
             # ---------------- Stage 2: Buck/Doe ----------------
-            buck_res = BUCK_DOE_MODEL(crop,conf=0.85, iou=0.40,agnostic_nms=True) 
+            buck_res = BUCK_DOE_MODEL(crop) 
             buck_probs = buck_res[0].probs
             top1_idx = buck_probs.top1
             buck_name = buck_res[0].names[top1_idx]
@@ -106,11 +106,11 @@ def process_image(image):
                 top1_type_idx = type_probs.top1
                 type_name = type_res[0].names[top1_type_idx]
                 type_conf = float(type_probs.top1conf)
-                label = f"Deer | Buck | {type_name} | {type_conf:.2f}"
+                label = f"Deer | Buck | {type_name}"
                 final_conf = type_conf
             else:
                 # Doe: use stage 2 confidence
-                label = f"Deer | Doe | {buck_conf:.2f}"
+                label = f"Deer | Doe "
                 final_conf = buck_conf
             detections.append({
                 "label": label,