Update app.py

app.py

@@ -1,7 +1,10 @@
 import gradio as gr
 from ultralytics import YOLO
 from huggingface_hub import hf_hub_download
+from PIL import Image, ImageDraw
+import numpy as np
 
+# Download model from your model repo
 model_path = hf_hub_download(
     repo_id="ProConceptTech/jambazisight",
     filename="best.pt"
@@ -10,23 +13,43 @@ model_path = hf_hub_download(
 model = YOLO(model_path)
 
 def detect(image):
-    results = model(image)
 
-    boxes = []
+    image = Image.fromarray(image)
+    results = model(image, conf=0.15)
+
+    detections = []
+    draw = ImageDraw.Draw(image)
+
     for r in results:
         for box in r.boxes:
-            boxes.append({
-                "class": int(box.cls),
-                "confidence": float(box.conf),
-                "bbox": box.xyxy.tolist()
+
+            x1, y1, x2, y2 = box.xyxy[0].tolist()
+            conf = float(box.conf)
+            cls = int(box.cls)
+            label = model.names[cls]
+
+            detections.append({
+                "class": label,
+                "confidence": conf,
+                "bbox": [x1, y1, x2, y2]
             })
 
-    return boxes
+            # draw bounding box
+            draw.rectangle([x1, y1, x2, y2], outline="red", width=3)
+            draw.text((x1, y1), f"{label} {conf:.2f}", fill="red")
+
+    return image, detections
+
 
 demo = gr.Interface(
     fn=detect,
-    inputs=gr.Image(type="pil"),
-    outputs="json"
+    inputs=gr.Image(type="numpy"),
+    outputs=[
+        gr.Image(label="Detected Image"),
+        gr.JSON(label="Detections")
+    ],
+    title="JambaziSight Object Detection API",
+    description="Upload an image to detect objects using the JambaziSight YOLO model."
 )
 
 demo.launch()