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Runtime error
| import gradio as gr | |
| import torch | |
| import torchvision | |
| import logging | |
| from detectron2.engine import DefaultPredictor | |
| import cv2 | |
| from detectron2.config import get_cfg | |
| from src.utils.visualizer import add_bboxes | |
| config_file="config.yaml" | |
| cfg = get_cfg() | |
| cfg.merge_from_file(config_file) | |
| cfg.MODEL.DEVICE="cpu" | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 | |
| cfg.MODEL.WEIGHTS = "checkpoints_model_final_imagenet_40k_synthetic.pth.pth" | |
| def predict( | |
| config_file, checkpoint_file, img_path | |
| ): | |
| predictor = DefaultPredictor(cfg) | |
| im = cv2.imread(img_path) | |
| output = predictor(im) | |
| img = add_bboxes(im, output['instances'].pred_boxes, scores=output['instances'].scores) | |
| return img | |
| title = "Pet Detection" | |
| description = "Demo for Indoor Pet Detection" | |
| examples = [['example.jpg']] | |
| gr.Interface(predict, inputs=gr.inputs.Image(type="file"), outputs=gr.outputs.Image(type="pil"),enable_queue=True, title=title, | |
| description=description, | |
| # article=article, | |
| examples=examples).launch() | |