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import gradio as gr | |
import torch | |
from PIL import Image | |
# Load the model using torch.hub (you must have the model locally) | |
model_name = "skin_burn_2022_8_21 (1).pt" | |
model =torch.hub.load("WongKinYiu/yolov7", 'custom',model_name) | |
def predict(img): | |
# Run inference with YOLO model | |
results = model(img) | |
# Convert the result to an image | |
result_img = Image.fromarray(results.render()) | |
return result_img | |
# Define a Gradio interface | |
iface = gr.Interface( | |
fn=predict, # the function to wrap | |
inputs=gr.inputs.Image(), # input type | |
outputs=gr.outputs.Image() # output type | |
) | |
iface.launch() | |