Upload 2 files

app.py

@@ -0,0 +1,56 @@
+# -*- coding: utf-8 -*-
+"""app
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1GzjDFYPEtsFsBFnhi3x3B0vWyCE-Dtpb
+"""
+
+import os
+from PIL import Image
+import gradio as gr
+from huggingface_hub import snapshot_download
+
+# Ensure necessary packages are installed
+try:
+    from ultralytics import YOLO
+except ImportError:
+    import subprocess
+    subprocess.check_call(["pip", "install", "ultralytics"])
+    from ultralytics import YOLO
+
+model_path = "/Users/markk/Downloads/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
+    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
+
+def predict_video(video_path):
+    result = detection_model.predict(video_path, conf=0.5, iou=0.6)
+    return result[0].save("output_video.mp4")  # Save processed video
+
+REPO_ID = "Lesterchia174/Monkey_Durian"
+detection_model = load_model(REPO_ID)
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil")
+).launch(share=True)
+
+# Process the new video file
+video_path = "Monkey_Durian.mp4"
+predict_video(video_path)

requirements.txt

@@ -0,0 +1,2 @@
+ultralytics
+huggingface_hub