init

.gitignore

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+*.pt

app.py

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+#%%
+import gradio as gr
+from ultralytics import YOLO
+import cv2
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "RandomCatLover/bird_detector"
+FILENAME = "best.pt"
+
+hf_hub_download(repo_id=REPO_ID, filename=FILENAME, local_dir=".")
+#%%
+yolo = YOLO("best.pt")
+
+def predict(img):
+    results = yolo(img)
+    for result in results:
+        try:
+            bbox = result.boxes.xyxy[0]
+        except:
+            continue
+        bbox = [int(i) for i in bbox]
+        img = cv2.rectangle(img, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 255, 0), 2)
+    return img
+#%%
+demo = gr.Interface(predict, 
+             "image", 
+             "image", 
+             examples=[
+                 f"imgs/{i}.jpg" for i in range(1,7)
+                 ],
+             cache_examples=True,
+             allow_flagging='never')
+
+demo.launch(debug=True)

requirements.txt

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+gradio==3.47.1
+huggingface_hub==0.18.0
+opencv_python==4.8.1.78
+ultralytics==8.0.198