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| import gradio as gr | |
| import cv2 | |
| import requests | |
| import os | |
| from PIL import Image | |
| import torch | |
| import ultralytics | |
| model = torch.hub.load("ultralytics/yolov5", "custom", path="yolov5_0.65map_exp7_best.pt", | |
| force_reload=False) | |
| model.conf = 0.20 # NMS confidence threshold | |
| path = [['img/test-image.jpg']] | |
| def show_preds_image(im): | |
| results = model(im) # inference | |
| return results.render()[0] | |
| inputs_image = [ | |
| gr.components.Image(type="filepath", label="Input Image"), | |
| ] | |
| outputs_image = [ | |
| gr.components.Image(type="filepath", label="Output Image"), | |
| ] | |
| interface_image = gr.Interface( | |
| fn=show_preds_image, | |
| inputs=inputs_image, | |
| outputs=outputs_image, | |
| title="Cashew Disease Detection", | |
| examples=path, | |
| cache_examples=False, | |
| ) | |
| interface_image.launch() |