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import re | |
import gradio as gr | |
from PIL import Image | |
def create_detection_tab(predict_fn, example_images): | |
with gr.TabItem("Breed Detection"): | |
gr.HTML("<p style='text-align: center;'>Upload a picture of a dog, and the model will predict its breed and provide detailed information!</p>") | |
gr.HTML("<p style='text-align: center; color: #666; font-size: 0.9em;'>Note: The model's predictions may not always be 100% accurate, and it is recommended to use the results as a reference.</p>") | |
with gr.Row(): | |
input_image = gr.Image(label="Upload a dog image", type="pil") | |
output_image = gr.Image(label="Annotated Image") | |
output = gr.HTML(label="Prediction Results") | |
initial_state = gr.State() | |
input_image.change( | |
predict_fn, | |
inputs=input_image, | |
outputs=[output, output_image, initial_state] | |
) | |
gr.Examples( | |
examples=example_images, | |
inputs=input_image | |
) | |
return { | |
'input_image': input_image, | |
'output_image': output_image, | |
'output': output, | |
'initial_state': initial_state | |
} | |