fix-demo (#1269)

demo/MMSegmentation_Tutorial.ipynb

@@ -48,9 +48,9 @@
    },
    "outputs": [],
    "source": [
-    "# Check nvcc version\r\n",
-    "!nvcc -V\r\n",
-    "# Check GCC version\r\n",
+    "# Check nvcc version\n",
+    "!nvcc -V\n",
+    "# Check GCC version\n",
     "!gcc --version"
    ]
   },
@@ -66,9 +66,9 @@
    },
    "outputs": [],
    "source": [
-    "# Install PyTorch\r\n",
-    "!pip install -U torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html\r\n",
-    "# Install MMCV\r\n",
+    "# Install PyTorch\n",
+    "!pip install -U torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html\n",
+    "# Install MMCV\n",
     "!pip install mmcv-full==latest+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html"
    ]
   },
@@ -84,9 +84,9 @@
    },
    "outputs": [],
    "source": [
-    "!rm -rf mmsegmentation\r\n",
-    "!git clone https://github.com/open-mmlab/mmsegmentation.git \r\n",
-    "%cd mmsegmentation\r\n",
+    "!rm -rf mmsegmentation\n",
+    "!git clone https://github.com/open-mmlab/mmsegmentation.git \n",
+    "%cd mmsegmentation\n",
     "!pip install -e ."
    ]
   },
@@ -102,12 +102,12 @@
    },
    "outputs": [],
    "source": [
-    "# Check Pytorch installation\r\n",
-    "import torch, torchvision\r\n",
-    "print(torch.__version__, torch.cuda.is_available())\r\n",
-    "\r\n",
-    "# Check MMSegmentation installation\r\n",
-    "import mmseg\r\n",
+    "# Check Pytorch installation\n",
+    "import torch, torchvision\n",
+    "print(torch.__version__, torch.cuda.is_available())\n",
+    "\n",
+    "# Check MMSegmentation installation\n",
+    "import mmseg\n",
     "print(mmseg.__version__)"
    ]
   },
@@ -132,7 +132,7 @@
    },
    "outputs": [],
    "source": [
-    "!mkdir checkpoints\r\n",
+    "!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"
    ]
   },
@@ -144,7 +144,7 @@
    },
    "outputs": [],
    "source": [
-    "from mmseg.apis import inference_segmentor, init_segmentor, show_result_pyplot\r\n",
+    "from mmseg.apis import inference_segmentor, init_segmentor, show_result_pyplot\n",
     "from mmseg.core.evaluation import get_palette"
    ]
   },
@@ -156,8 +156,8 @@
    },
    "outputs": [],
    "source": [
-    "config_file = 'configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py'\r\n",
-    "checkpoint_file = 'checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'"
+    "config_file = '../configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py'\n",
+    "checkpoint_file = '../checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'"
    ]
   },
   {
@@ -172,7 +172,7 @@
    },
    "outputs": [],
    "source": [
-    "# build the model from a config file and a checkpoint file\r\n",
+    "# build the model from a config file and a checkpoint file\n",
     "model = init_segmentor(config_file, checkpoint_file, device='cuda:0')"
    ]
   },
@@ -185,7 +185,7 @@
    "outputs": [],
    "source": [
     "# test a single image\n",
-    "img = 'demo/demo.png'\n",
+    "img = './demo.png'\n",
     "result = inference_segmentor(model, img)"
    ]
   },
@@ -202,7 +202,7 @@
    },
    "outputs": [],
    "source": [
-    "# show the results\r\n",
+    "# show the results\n",
     "show_result_pyplot(model, img, result, get_palette('cityscapes'))"
    ]
   },
@@ -248,8 +248,8 @@
    },
    "outputs": [],
    "source": [
-    "# download and unzip\r\n",
-    "!wget http://dags.stanford.edu/data/iccv09Data.tar.gz -O standford_background.tar.gz\r\n",
+    "# download and unzip\n",
+    "!wget http://dags.stanford.edu/data/iccv09Data.tar.gz -O standford_background.tar.gz\n",
     "!tar xf standford_background.tar.gz"
    ]
   },
@@ -266,13 +266,13 @@
    },
    "outputs": [],
    "source": [
-    "# Let's take a look at the dataset\r\n",
-    "import mmcv\r\n",
-    "import matplotlib.pyplot as plt\r\n",
-    "\r\n",
-    "img = mmcv.imread('iccv09Data/images/6000124.jpg')\r\n",
-    "plt.figure(figsize=(8, 6))\r\n",
-    "plt.imshow(mmcv.bgr2rgb(img))\r\n",
+    "# Let's take a look at the dataset\n",
+    "import mmcv\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "img = mmcv.imread('iccv09Data/images/6000124.jpg')\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "plt.imshow(mmcv.bgr2rgb(img))\n",
     "plt.show()"
    ]
   },
@@ -414,7 +414,7 @@
    "outputs": [],
    "source": [
     "from mmcv import Config\n",
-    "cfg = Config.fromfile('configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py')"
+    "cfg = Config.fromfile('../configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py')"
    ]
   },
   {
@@ -620,8 +620,21 @@
   },
   "kernelspec": {
    "display_name": "Python 3",
+   "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": "3.7.0"
+  },
   "pycharm": {
    "stem_cell": {
     "cell_type": "raw",