app.py, model, image added!

app..py

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+import gradio as gr
+import cv2
+import requests
+import os
+
+from ultralytics import YOLO
+
+file_urls = [
+    "https://www.dropbox.com/scl/fi/2mlc191y9lzbe8nwu45ss/duck76.jpeg?rlkey=qwnr78mtdy7sjg71ldrui6vf0&dl=0",
+    "https://www.dropbox.com/scl/fi/2y4cdkwwn3drlh4ob86ic/duck85.jpeg?rlkey=lcl3n0jav7ougsj4tamm1hh93&dl=0",
+    "https://www.dropbox.com/scl/fi/8gojxnm8wwhs2isj6k4zv/duck23.jpeg?rlkey=2zioinhr0wfpv22qq963tnv8a&dl=0",
+]
+
+def download_file(url, save_name):
+    if not os.path.exists(save_name):
+        file = requests.get(url)
+        open(save_name, "wb").write(file.content)
+
+for i, url in enumerate(file_urls):
+    if "mp4" in url:
+        download_file(url, "video.mp4")
+    else:
+        download_file(url, f"image_{i}.jpg")
+
+model = YOLO("best.pt")
+
+def show_preds_image(image):
+    outputs = model.predict(source=image)
+    image_np = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    results = outputs.xyxy[0].cpu().numpy()
+
+    for det in results:
+        cv2.rectangle(
+            image_np,
+            (int(det[0]), int(det[1])),
+            (int(det[2]), int(det[3])),
+            color=(0, 0, 255),
+            thickness=2,
+            lineType=cv2.LINE_AA,
+        )
+    return cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
+
+inputs_image = gr.inputs.Image(type="file", label="Input Image")
+outputs_image = gr.outputs.Image(type="numpy", label="Output Image")
+interface_image = gr.Interface(
+    fn=show_preds_image,
+    inputs=inputs_image,
+    outputs=outputs_image,
+    title="Duck Image Segmentation",
+    examples=file_urls,
+    allow_flagging=False,
+)
+
+interface_image.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b71d65569e7091a1bd20581881c6709d6312db127c33131fd89dcaf3bd091cdc
+size 6788323