initial commit

.gitignore

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+best.pt
+examples/

app.py

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+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+
+model = YOLO("./best.pt")
+
+
+def process_img(img: gr.Image):
+    result = model.predict(img)
+    for r in result:
+        im_bgr = r.plot()
+        return gr.Image(
+            label="Output Image with labels", value=Image.fromarray(im_bgr[..., ::-1])
+        )
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(value="Port Classification App")
+
+    with gr.Row():
+        with gr.Column():
+            upload_img = gr.Image(label="Upload Image", type="pil")
+            classify_img_button = gr.Button(value="Process Image")
+
+        with gr.Column():
+            output_img = gr.Image(label="Output Image with labels")
+    with gr.Row():
+        gr.Examples(
+            examples=[
+                "./examples/01.jpg",
+                "./examples/02.jpg",
+                "./examples/03.jpg",
+                "./examples/04.jpg",
+                "./examples/05.jpg",
+                "./examples/06.jpg",
+            ],
+            inputs=upload_img
+        )
+    classify_img_button.click(fn=process_img, inputs=upload_img, outputs=output_img)
+
+    demo.launch(server_name="0.0.0.0", server_port=7777)

requirements.txt

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+ultralytics
+pillow
+gradio