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import gradio as gr
from fastai.vision.all import *
from fastcore.all import *
learn = load_learner("model_cow (1).pkl")
categories = ('Angus', 'Brown Swiss', 'Charolais', 'Hereford', 'Holstein', 'Jersey', 'Limousin', 'Simmental')
def classify_img(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
with gr.Blocks(title = " what kind of cow ") as demo:
with gr.Row():
gr.Markdown("""
### what kind of cow ?
#### click on the photos and then click "PREDİCT" button.
""")
with gr.Row():
image = gr.inputs.Image(shape=(192,192))
with gr.Row():
output = gr.outputs.Label()
with gr.Row():
image_button = gr.Button("PREDİCT")
image_button.click(classify_img, inputs=image, outputs=output)
with gr.Row():
with gr.Column():
gr.Examples(inputs=image,examples=["1.jpg"],label="angus")
with gr.Column():
gr.Examples(inputs=image,examples=["2.jpg"],label="brown swiss")
with gr.Column():
gr.Examples(inputs=image,examples=["3.jpg"],label="simmental")
with gr.Column():
gr.Examples(inputs=image,examples=["7.jpg"],label="jersey")
with gr.Column():
gr.Examples(inputs=image,examples=["5.jpg"],label="Angus")
with gr.Column():
gr.Examples(inputs=image,examples=["6.jpg"],label="brown swiss")
with gr.Column():
gr.Examples(inputs=image,examples=["4.jpg"],label="simmental")
with gr.Column():
gr.Examples(inputs=image,examples=["8.jpg"],label="angus")
demo.launch() |