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Runtime error
| #try: | |
| # import detectron2 | |
| #except: | |
| import os | |
| os.system('pip install git+https://github.com/SysCV/transfiner.git') | |
| from matplotlib.pyplot import axis | |
| import gradio as gr | |
| import requests | |
| import numpy as np | |
| from torch import nn | |
| import requests | |
| import torch | |
| from detectron2 import model_zoo | |
| from detectron2.engine import DefaultPredictor | |
| from detectron2.config import get_cfg | |
| from detectron2.utils.visualizer import Visualizer | |
| from detectron2.data import MetadataCatalog | |
| model_name='./configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x_4gpu_transfiner.yaml' | |
| cfg = get_cfg() | |
| # add project-specific config (e.g., TensorMask) here if you're not running a model in detectron2's core library | |
| cfg.merge_from_file(model_name) | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # set threshold for this model | |
| # Find a model from detectron2's model zoo. You can use the https://dl.fbaipublicfiles... url as w ell | |
| cfg.MODEL.WEIGHTS = './output_3x_transfiner_r50.pth' | |
| if not torch.cuda.is_available(): | |
| cfg.MODEL.DEVICE='cpu' | |
| predictor = DefaultPredictor(cfg) | |
| def inference(image): | |
| #image = image.resize((1024,1024)) | |
| img = np.asarray(image) | |
| #img = np.array(image) | |
| outputs = predictor(img) | |
| v = Visualizer(img, MetadataCatalog.get(cfg.DATASETS.TRAIN[0])) | |
| out = v.draw_instance_predictions(outputs["instances"].to("cpu")) | |
| return out.get_image() | |
| title = "Mask Transfiner [CVPR, 2022]" | |
| description = "Demo for <a target='_blank' href='https://arxiv.org/abs/2111.13673'>Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022</a> based on R50-FPN. To use it, simply upload your image, or click one of the examples to load them. It runs in the cpu environment provided by Hugging Face. Read more at the links below." | |
| article = "<p style='text-align: center'><a target='_blank' href='https://arxiv.org/abs/2111.13673'>Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022</a> | <a target='_blank' href='https://github.com/SysCV/transfiner'>Mask Transfiner Github</a></p>" | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Image(type="pil", label="Input")], | |
| gr.outputs.Image(type="numpy", label="Output"), | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=[ | |
| ["demo/sample_imgs/000000131444.jpg"], | |
| ["demo/sample_imgs/000000157365.jpg"], | |
| ["demo/sample_imgs/000000176037.jpg"], | |
| ["demo/sample_imgs/000000018737.jpg"], | |
| ["demo/sample_imgs/000000224200.jpg"], | |
| ["demo/sample_imgs/000000558073.jpg"], | |
| ["demo/sample_imgs/000000404922.jpg"], | |
| ["demo/sample_imgs/000000252776.jpg"], | |
| ["demo/sample_imgs/000000482477.jpg"], | |
| ["demo/sample_imgs/000000344909.jpg"] | |
| ]).launch() | |