Spaces:
Running
Running
File size: 915 Bytes
416724a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 |
import gradio as gr
import torch
from PIL import Image
from ultralytics import YOLO
model = YOLO(r'pcb-best.pt')
def predict(img, conf, iou):
results = model.predict(img, conf=conf, iou=iou)
for i, r in enumerate(results):
# Plot results image
im_bgr = r.plot() # BGR-order numpy array
im_rgb = Image.fromarray(im_bgr[..., ::-1]) # RGB-order PIL image
# Show results to screen (in supported environments)
return im_rgb
base_conf, base_iou = 0.25, 0.45
title = "基于YOLO-V8的PCB电路板缺陷检测"
des = "鼠标点击上传图片即可检测缺陷,可通过鼠标调整预测置信度,还可点击网页最下方示例图片进行预测"
gr.Interface(inputs=['image',gr.Slider(maximum=1, minimum=0, value=base_conf), gr.Slider(maximum=1, minimum=0, value=base_iou)],
outputs=["image"], fn=predict, title=title, description=des).launch()
|