Upload app.py

app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[4]:
+
+
+from ultralytics import YOLO
+from PIL import Image
+import gradio as gr
+from huggingface_hub import snapshot_download
+import os
+
+model_path = "best_int8_openvino_model"
+
+def load_model(repo_id):
+    download_dir = snapshot_download(repo_id)
+    print(download_dir)
+    path  = os.path.join(download_dir, "best_int8_openvino_model")
+    print(path)
+    detection_model = YOLO(path, task='detect')
+    return detection_model
+
+
+def predict(pilimg):
+
+    source = pilimg
+    # x = np.asarray(pilimg)
+    # print(x.shape)
+    result = detection_model.predict(source, conf=0.4, iou=0.6)
+    img_bgr = result[0].plot()
+    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
+    
+    return out_pilimg
+
+
+REPO_ID = "ITI107-2024S2/8035531F"
+detection_model = load_model(REPO_ID)
+
+title = "Detect Durian and Mangosteen (King and Queen of Fruits) In The Image"
+interface = gr.Interface(
+                fn=predict,
+                inputs=gr.Image(type="pil", label="Input Image"),
+                outputs=gr.Image(type="pil", label="Object Detected Image"),
+                title=title,
+             )
+
+# Launch the interface
+interface.launch(share=True)
+
+
+# In[ ]:
+
+
+
+