.env file with settings for Docker

.dockerignore

@@ -0,0 +1 @@
+*

.env

@@ -0,0 +1 @@
+HOME=/app

Dockerfile

@@ -1,5 +1,6 @@
 # modified from  https://hub.docker.com/r/cwaffles/openpose
 FROM nvidia/cuda:11.4.0-cudnn8-devel-ubuntu20.04
+#FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
 
 #get deps
 RUN apt-get update && \
@@ -32,10 +33,23 @@ RUN make install
 RUN cp /openpose/build/python/openpose/pyopenpose.cpython-38-x86_64-linux-gnu.so /usr/local/lib/python3.8/dist-packages/
 WORKDIR /usr/local/lib/python3.8/dist-packages
 RUN ln -s pyopenpose.cpython-38-x86_64-linux-gnu.so pyopenpose
+#RUN cp /openpose/build/python/openpose/pyopenpose.cpython-310-x86_64-linux-gnu.so /usr/local/lib/python3.10/dist-packages/
+#WORKDIR /usr/local/lib/python3.10/dist-packages
+#RUN ln -s pyopenpose.cpython-310-x86_64-linux-gnu.so pyopenpose
 #ENV LD_LIBRARY_PATH=/openpose/build/python/openpose
 
 RUN apt-get install -y ffmpeg
 
-WORKDIR /openpose
+# Notebook to actually run code
+#RUN apt-get install -y python3-notebook
+RUN pip install ipywidgets  --ignore-installed
+RUN pip install notebook
+RUN pip install ipywebrtc
+EXPOSE 8888
 
+# Possibly, use /home/user/app & set HOME to /home/user to avoid temporary directories in the app folder (if desired)
+WORKDIR /app
+ENV HOME /app
+#CMD ["env"]
+CMD ["jupyter", "notebook", "--ip", "0.0.0.0"]
 

app/openpose.ipynb

@@ -0,0 +1,433 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4268bbde",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#hide\n",
+    "import pyopenpose as op\n",
+    "import ipywidgets\n",
+    "from ipywebrtc import CameraStream\n",
+    "import cv2 \n",
+    " "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9b530e24",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Defaulting to user installation because normal site-packages is not writeable\n",
+      "Requirement already satisfied: tqdm in ./.local/lib/python3.8/site-packages (4.64.1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip3 install tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "47bbe21b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " from tqdm.notebook import tqdm\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8185becc",
+   "metadata": {},
+   "source": [
+    "# Jupyter notebook for OpenPose experiments\n",
+    "\n",
+    "Read any image or video from the `/data` directory and render the output here "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cb916658",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wed Nov  2 15:54:10 2022       \r\n",
+      "+-----------------------------------------------------------------------------+\r\n",
+      "| NVIDIA-SMI 470.141.03   Driver Version: 470.141.03   CUDA Version: 11.4     |\r\n",
+      "|-------------------------------+----------------------+----------------------+\r\n",
+      "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\r\n",
+      "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\r\n",
+      "|                               |                      |               MIG M. |\r\n",
+      "|===============================+======================+======================|\r\n",
+      "|   0  NVIDIA GeForce ...  On   | 00000000:08:00.0 Off |                  N/A |\r\n",
+      "|  0%   41C    P5    61W / 350W |     21MiB / 24265MiB |      0%      Default |\r\n",
+      "|                               |                      |                  N/A |\r\n",
+      "+-------------------------------+----------------------+----------------------+\r\n",
+      "                                                                               \r\n",
+      "+-----------------------------------------------------------------------------+\r\n",
+      "| Processes:                                                                  |\r\n",
+      "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\r\n",
+      "|        ID   ID                                                   Usage      |\r\n",
+      "|=============================================================================|\r\n",
+      "+-----------------------------------------------------------------------------+\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!nvidia-smi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5222af69",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# CameraStream.facing_user(audio=False)\n",
+    "# requires SSL website... :-("
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "266062c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "params = dict()\n",
+    "params[\"model_folder\"] = \"/openpose/models/\"\n",
+    "# params[\"face\"] = True\n",
+    "params[\"hand\"] = True\n",
+    "# params[\"heatmaps_add_parts\"] = True\n",
+    "# params[\"heatmaps_add_bkg\"] = True\n",
+    "# params[\"heatmaps_add_PAFs\"] = True\n",
+    "# params[\"heatmaps_scale\"] = 3\n",
+    "# params[\"upsampling_ratio\"] = 1\n",
+    "# params[\"body\"] = 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f034fee8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Starting OpenPose Python Wrapper...\n",
+      "Auto-detecting all available GPUs... Detected 1 GPU(s), using 1 of them starting at GPU 0.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Starting OpenPose\n",
+    "opWrapper = op.WrapperPython()\n",
+    "opWrapper.configure(params)\n",
+    "opWrapper.start()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "37f999b3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# upload = ipywidgets.FileUpload()\n",
+    "# display(upload)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "de658948",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "1b4208da",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# # Process Image\n",
+    "# datum = op.Datum()\n",
+    "# imageToProcess = cv2.imread(args[0].image_path)\n",
+    "# datum.cvInputData = imageToProcess\n",
+    "# opWrapper.emplaceAndPop(op.VectorDatum([datum]))\n",
+    "\n",
+    "# # Display Image\n",
+    "# print(\"Body keypoints: \\n\" + str(datum.poseKeypoints))\n",
+    "# print(\"Face keypoints: \\n\" + str(datum.faceKeypoints))\n",
+    "# print(\"Left hand keypoints: \\n\" + str(datum.handKeypoints[0]))\n",
+    "# print(\"Right hand keypoints: \\n\" + str(datum.handKeypoints[1]))\n",
+    "# cv2.imwrite(\"/data/result_body.jpg\",datum.cvOutputData)\n",
+    "\n",
+    "# print(dir(datum))\n",
+    "# #    cv2.imshow(\"OpenPose 1.7.0 - Tutorial Python API\", datum.cvOutputData)\n",
+    "#    cv2.waitKey(0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3c994aa0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "402ad8b9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "275242c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Frames per second :  24.0 FPS\n",
+      "Frame count :  500.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "vid_capture = cv2.VideoCapture('/data/0001-0500.mp4')\n",
+    "\n",
+    "# Create a video capture object, in this case we are reading the video from a file\n",
+    "if (vid_capture.isOpened() == False):\n",
+    "  print(\"Error opening the video file\")\n",
+    "# Read fps and frame count\n",
+    "else:\n",
+    "  # Get frame rate information\n",
+    "  # You can replace 5 with CAP_PROP_FPS as well, they are enumerations\n",
+    "  fps = vid_capture.get(5)\n",
+    "  print('Frames per second : ', fps,'FPS')\n",
+    " \n",
+    "  # Get frame count\n",
+    "  # You can replace 7 with CAP_PROP_FRAME_COUNT as well, they are enumerations\n",
+    "  frame_count = vid_capture.get(7)\n",
+    "  print('Frame count : ', frame_count)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "b0149d40",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "frame_size = (int(vid_capture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(vid_capture.get(cv2.CAP_PROP_FRAME_HEIGHT\n",
+    ")))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "2a536a5f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1920, 1080)"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "frame_size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "66003b23",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "output = cv2.VideoWriter(\n",
+    "    '/data/output.mp4',\n",
+    "    # see http://mp4ra.org/#/codecs for codecs\n",
+    "#     cv2.VideoWriter_fourcc('m','p','4','v'),\n",
+    "#      cv2.VideoWriter_fourcc(*'mp4v'),\n",
+    "#     cv2.VideoWriter_fourcc('a','v','1','C'),\n",
+    "    cv2.VideoWriter_fourcc(*'vp09'),\n",
+    "#     cv2.VideoWriter_fourcc(*'avc1'),\n",
+    "    fps,\n",
+    "    frame_size)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "6ed91535",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "633b01b6f8474017ab2ba3d454b3adea",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/500.0 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Stream ended\n"
+     ]
+    }
+   ],
+   "source": [
+    "# See also:\n",
+    "# with tqdm.wrapattr(file_obj, \"read\", total=file_obj.size) as fobj:\n",
+    "# ...     while True:\n",
+    "# ...         chunk = fobj.read(chunk_size)\n",
+    "# ...         if not chunk:\n",
+    "# ...             break\n",
+    "t = tqdm(total=frame_count) # Initialise\n",
+    "while(vid_capture.isOpened()):\n",
+    "    t.update(1)\n",
+    "# with tqdm.wrapattr(vid_capture, \"read\", total=frame_count) as vid_obj:\n",
+    "#     # vid_capture.read() methods returns a tuple, first element is a bool \n",
+    "    # and the second is frame\n",
+    "#     while True:\n",
+    "    ret, frame = vid_capture.read()\n",
+    "    if ret == True:\n",
+    "        datum = op.Datum()\n",
+    "        datum.cvInputData = frame\n",
+    "        opWrapper.emplaceAndPop(op.VectorDatum([datum]))\n",
+    "\n",
+    "        # Display Image\n",
+    "        # print(\"Body keypoints: \\n\" + str(datum.poseKeypoints))\n",
+    "        # print(\"Face keypoints: \\n\" + str(datum.faceKeypoints))\n",
+    "        # print(\"Left hand keypoints: \\n\" + str(datum.handKeypoints[0]))\n",
+    "        # print(\"Right hand keypoints: \\n\" + str(datum.handKeypoints[1]))\n",
+    "        #cv2.imwrite(f\"/data/out/result_body_scale{i:03d}.jpg\",datum.cvOutputData)\n",
+    "        output.write(datum.cvOutputData)\n",
+    "    else:\n",
+    "        print(\"Stream ended\")\n",
+    "        break\n",
+    "t.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "27580409",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Release the objects\n",
+    "vid_capture.release()\n",
+    "output.release()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "6f3ad121",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9b632f75a46f4306bcadddf38ac4887e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Video(value=b'\\x00\\x00\\x00\\x1cftypisom\\x00\\x00\\x02\\x00isomiso2mp41\\x00\\x00\\x00\\x08free\\x00U\\x0c\\xe0...')"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# display(HTML(\"\"\"<video width=\"100\" height=\"100\" controls><source src=\"/data/output.mp4\" type=\"video/mp4\"></video>\"\"\"))\n",
+    "ipywidgets.Video.from_file('/data/outputs.mp4')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6d97230b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from IPython.display import Video\n",
+    "# Video('/data/outputs.mp4', embed=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0b462645",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docker-compose.yml

@@ -0,0 +1,21 @@
+version: "3.3"
+services:
+  suspicion_nb:
+    image: suspicion_nb
+    restart: always
+    build:
+      context: .
+      dockerfile: ./Dockerfile
+    user: "1000:1000"
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    ports:
+      - "8888:8888"
+    volumes:
+      - ./data:/data
+      - ./app:/app