Update app.py

app.py

@@ -1,30 +1,30 @@
-from ultralytics import YOLO
-from PIL import Image
-import gradio as gr
-from huggingface_hub import snapshot_download
-import os
-
-def load_model(repo_id):
-    detection_model = YOLO('best.pt', task='detect')
-    return detection_model
-
-
-def predict(pilimg):
-
-    source = pilimg
-    # x = np.asarray(pilimg)
-    # print(x.shape)
-    result = detection_model.predict(source, conf=0.5, iou=0.6)
-    img_bgr = result[0].plot()
-    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
-    
-    return out_pilimg
-
-
-REPO_ID = "ITI107-2024S2/7821983W-lowboonsiong"
-detection_model = load_model(REPO_ID)
-
-gr.Interface(fn=predict,
-             inputs=gr.Image(type="pil"),
-             outputs=gr.Image(type="pil")
+from ultralytics import YOLO
+from PIL import Image
+import gradio as gr
+from huggingface_hub import snapshot_download
+import os
+
+def load_model(repo_id):
+    detection_model = YOLO('best.pt', task='detect')
+    return detection_model
+
+
+def predict(pilimg):
+
+    source = pilimg
+    # x = np.asarray(pilimg)
+    # print(x.shape)
+    result = detection_model.predict(source, conf=0.5, iou=0.6)
+    img_bgr = result[0].plot()
+    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
+    
+    return out_pilimg
+
+
+REPO_ID = "lowboonsiong/ITC110"
+detection_model = load_model(REPO_ID)
+
+gr.Interface(fn=predict,
+             inputs=gr.Image(type="pil"),
+             outputs=gr.Image(type="pil")
              ).launch(share=True)