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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()
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