source entrypoint.h before running the notebook

README.md

@@ -68,6 +68,11 @@ To prevent the repo from growing in size, recommend always "restart and clear ou
 
 ### Build on conda
 
+Installation using the following command
 ```
 pip3 install -r requirements.txt -f https://download.pytorch.org/whl/torch_stable.html
+```
+Using the environment through the following command
+```
+source docker/entrypoint.sh
 ```

dense_correspondence/dataset/simple_datasets_test.ipynb

@@ -27,15 +27,28 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.append(\"../..\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Using SpartanDataset:\n",
-      "   - in train mode\n",
-      "   - number of scenes 11\n",
-      "   - total images:     2851\n"
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'pytorch_segmentation_detection'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_5273/718444074.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mspartan_dataset_masked\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mSpartanDataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdense_correspondence_manipulation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mutils\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_dense_correspondence_to_python_path\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdense_correspondence\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_tools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_finder\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcorrespondence_finder\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/pytorch-dense-correspondence/dense_correspondence/dataset/spartan_dataset_masked.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mdense_correspondence\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdense_correspondence_dataset_masked\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mDenseCorrespondenceDataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mImageType\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mlogging\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/pytorch-dense-correspondence/dense_correspondence/dataset/dense_correspondence_dataset_masked.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mtorchvision\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtransforms\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mpytorch_segmentation_detection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransforms\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mComposeJoint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     21\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdense_correspondence\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_tools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_finder\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcorrespondence_finder\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdense_correspondence\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_tools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorrespondence_augmentation\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mcorrespondence_augmentation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pytorch_segmentation_detection'"
      ]
     }
    ],
@@ -185,7 +198,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -199,7 +212,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.7.11"
   }
  },
  "nbformat": 4,

docker/entrypoint.sh

@@ -1,9 +1,9 @@
 #!/bin/bash
 set -e
 
-export DATA_DIR=~/data
+export DATA_DIR=~/pytorch-dense-correspondence/data
 export DC_DATA_DIR=$DATA_DIR/pdc
-export DC_SOURCE_DIR=~/code
+export DC_SOURCE_DIR=~/pytorch-dense-correspondence
 export PDC_BUILD_DIR=$DC_SOURCE_DIR/build
 export POSER_BUILD_DIR=$PDC_BUILD_DIR/poser
 

requirements.txt

@@ -19,4 +19,5 @@ plyfile
 pandas
 tensorflow
 future
-typing
+typing
+pyyaml