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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!mkdir ../checkpoints\n",
"!wget https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth -P ../checkpoints"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"is_executing": true
}
},
"outputs": [],
"source": [
"import torch\n",
"import matplotlib.pyplot as plt\n",
"from mmengine.model.utils import revert_sync_batchnorm\n",
"from mmseg.apis import init_model, inference_model, show_result_pyplot"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"is_executing": true
}
},
"outputs": [],
"source": [
"config_file = '../configs/pspnet/pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.py'\n",
"checkpoint_file = '../checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# build the model from a config file and a checkpoint file\n",
"model = init_model(config_file, checkpoint_file, device='cpu')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# test a single image\n",
"img = 'demo.png'\n",
"if not torch.cuda.is_available():\n",
" model = revert_sync_batchnorm(model)\n",
"result = inference_model(model, img)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# show the results\n",
"vis_result = show_result_pyplot(model, img, result, show=False)\n",
"plt.imshow(vis_result)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "pt1.13",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
},
"pycharm": {
"stem_cell": {
"cell_type": "raw",
"metadata": {
"collapsed": false
},
"source": []
}
},
"vscode": {
"interpreter": {
"hash": "f61d5b8fecdd960739697f6c2860080d7b76a5be5d896cb034bdb275ab3ddda0"
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"nbformat": 4,
"nbformat_minor": 4
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