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| import gradio as gr | |
| import yolov5 | |
| # load model | |
| model = yolov5.load('keremberke/yolov5m-license-plate') | |
| # set model parameters | |
| model.conf = 0.5 # NMS confidence threshold | |
| model.iou = 0.25 # NMS IoU threshold | |
| model.agnostic = False # NMS class-agnostic | |
| model.multi_label = False # NMS multiple labels per box | |
| model.max_det = 1000 # maximum number of detections per image | |
| def greet(img): | |
| results = model(img, size=640) | |
| return "Hello " + str(results.pred) + "!!" | |
| iface = gr.Interface(fn=greet, inputs="image", outputs="text") | |
| iface.launch() |