Create app.py

app.py

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+#import gradio as gr
+#from ultralytics import YOLO
+
+#def greet(name):
+#    return "Hello " + name + "!!"
+
+#demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+#demo.launch()
+
+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=0.5, iou=0.6)
+    img_bgr = result[0].plot()
+    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
+    
+    return out_pilimg
+
+
+#REPO_ID = "Jason-NYP/6304871K"
+REPO_ID = "ITI107-2024S2/6304871K"
+detection_model = load_model(REPO_ID)
+
+gr.Interface(fn=predict,
+             inputs=gr.Image(type="pil"),
+             outputs=gr.Image(type="pil")
+             ).launch(share=True)