| import gradio as gr | |
| import yolov5 | |
| import os | |
| from transformers import pipeline | |
| #ImageClassifier = pipeline(task="image-classification", model="") | |
| model = yolov5.load('./gentle-meadow.pt', device='cpu') | |
| def predict(image): | |
| results = model([image], size=224) | |
| #predictions = imageClassifier(image) | |
| # classMappings = { | |
| # 'police': "Police / Authorized Personnel", | |
| # 'public': 'Unauthorized Person' | |
| # } | |
| # output = {} | |
| # for item in predictions: | |
| # output[classMappings[item['label']]] = item['score'] | |
| return results.render()[0] | |
| demo = gr.Interface(fn=predict, | |
| inputs=gr.inputs.Image(type="pil"), | |
| outputs=gr.outputs.Image(type="pil"), | |
| ) | |
| demo.launch() |