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import gradio as gr | |
from ultralytics import YOLO | |
import torch | |
# model = YOLO('best.pt') | |
path = 'best.pt' | |
model = torch.hub.load("WongKinYiu/yolov7","custom",path,trust_repo=True) | |
# model = torch.hub.load('WongKinYiu/yolov7', 'custom', 'best.pt', force_reload=True, source='local', trust_repo=True) | |
def predict(input_image): | |
""" | |
Predict model output | |
""" | |
# 使用模型進行預測 | |
output = model(input_image) | |
# 將模型輸出轉為可讀的文字,這部分需要依據你的模型輸出的實際格式進行處理 | |
price = str(output) | |
return [output, price] | |
with gr.Blocks() as demo: | |
# Title | |
gr.Markdown( | |
""" | |
<h1 align="center">AI Cafeteria Price Evaluator</h1> | |
""") | |
# Model Evaluation | |
gr.Interface( | |
fn=predict, | |
inputs=gr.Image(type="pil"), | |
outputs=[gr.Image(type="pil", label="Image Prediction"), | |
gr.Textbox(type="text", label="Price Prediction")] | |
) | |
if __name__ == "__main__": | |
demo.launch() | |