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Runtime error
| import os | |
| os.system('pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu102/torch1.9/index.html') | |
| os.system('pip install torch==1.9.0 torchvision==0.10.0') | |
| import gradio as gr | |
| # check pytorch installation: | |
| import torch, torchvision | |
| print(torch.__version__, torch.cuda.is_available()) | |
| assert torch.__version__.startswith("1.9") # please manually install torch 1.9 if Colab changes its default version | |
| import detectron2 | |
| from detectron2.utils.logger import setup_logger | |
| import numpy as np | |
| import os, json, random | |
| from detectron2 import model_zoo | |
| from detectron2.engine import DefaultPredictor | |
| from detectron2.config import get_cfg | |
| from PIL import Image | |
| from pathlib import Path | |
| from matplotlib import pyplot as plt | |
| cfg = get_cfg() | |
| cfg.MODEL.DEVICE='cpu' | |
| cfg.INPUT.MASK_FORMAT='bitmask' | |
| cfg.MODEL.ROI_HEADS.NUM_CLASSES = 3 | |
| cfg.TEST.DETECTIONS_PER_IMAGE = 1000 | |
| cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")) | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # set threshold for this model | |
| cfg.MODEL.WEIGHTS = "model_final.pth" | |
| predictor = DefaultPredictor(cfg) | |
| def inference(img): | |
| class_names = ['0','1','2'] #['astro', 'cort', 'sh-sy5y'] | |
| im = np.asarray(Image.open(img).convert('RGB')) | |
| outputs = predictor(im) | |
| pred_classes = outputs['instances'].pred_classes.cpu().numpy().tolist() | |
| take = outputs['instances'].scores >= 0.5 #Threshold | |
| pred_masks = outputs['instances'].pred_masks[take].cpu().numpy() | |
| pred_class = max(set(pred_classes), key=pred_classes.count) | |
| mask = np.stack(pred_masks) | |
| mask = np.any(mask == 1, axis=0) | |
| p = plt.imshow(im,cmap='gray') | |
| p = plt.imshow(mask, alpha=0.4) | |
| p = plt.xticks(fontsize=8) | |
| p = plt.yticks(fontsize=8) | |
| p = plt.title("cell type: " + class_names[pred_class]) | |
| return plt | |
| title = "Sartorius Cell Instance Segmentation" | |
| description = "Sartorius Cell Instance Segmentation Demo: Current Kaggle competition - kaggle.com/c/sartorius-cell-instance-segmentation" | |
| article = "<p style='text-align: center'><a href='https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/' target='_blank'>Detectron2: A PyTorch-based modular object detection library</a> | <a href='https://github.com/facebookresearch/detectron2' target='_blank'>Github Repo</a></p>" | |
| examples = [['0030fd0e6378.png']] | |
| gr.Interface(inference, inputs=gr.inputs.Image(type="filepath"), outputs=gr.outputs.Image('plot') ,enable_queue=True, title=title, | |
| description=description, | |
| article=article, | |
| examples=examples).launch(debug=False) | |