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Installation script for facebookresearch / pifuhd
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| #!/bin/bash | |
| minVersion="$(python3 -V 2>&1 | grep -Po '(?<=Python 3\.)([0-9]+)')" | |
| if (( "$minVersion" <= 5 )); then | |
| echo "You're python version is too old. You need at least Python 3.6.x" >&2 | |
| echo "Try the following: " | |
| echo " sudo add-apt-repository ppa:deadsnakes/ppa" | |
| echo " sudo apt update" | |
| echo " sudo apt upgrade" | |
| echo " sudo apt install python3.8 python3.8-venv python3.8-dev python3.8-gdbm" | |
| echo "Then make sure that Python 3.8 is the default interpreter by either configuring update-alternatives or using an alias in your .bashrc." | |
| echo "You can find more information here: https://medium.com/analytics-vidhya/installing-python-3-8-3-66701d3db134" | |
| exit 1 | |
| fi | |
| installPath="$(pwd)" | |
| if [ -n "$1" ]; then | |
| mkdir -p "$1" || exit 1 | |
| installPath="(realpath "$1")" | |
| fi | |
| extraPackages=( | |
| "liboctomap-dev" | |
| "libfcl-dev" | |
| "libspatialindex-dev" | |
| "libgl1-mesa-glx" | |
| ) | |
| installPackages=() | |
| for package in "${extraPackages[@]}"; do | |
| if ! dpkg-query -W -f='${Status}\n' "$package" 2>/dev/null | grep -q "install ok"; then | |
| installPackages+=("$package") | |
| fi | |
| done | |
| if (( "${#installPackages[@]}" > 0 )); then | |
| echo "The following additional packages are needed for trimesh[all], rtree and opencv2: ${installPackages[@]}" | |
| sudo apt install "${installPackages[@]}" || exit 1 | |
| fi | |
| versionError=false | |
| fclVersion="$(dpkg-query -W -f='${Version}\n' libfcl-dev)" | |
| if ! [[ "$fclVersion" =~ ^0\.5.* ]]; then | |
| echo "libfcl-dev is only available in version $fclVersion but we need at least version 0.5.0." >&2 | |
| versionError=true | |
| fi | |
| octoVersion="$(dpkg-query -W -f='${Version}\n' liboctomap-dev)" | |
| if ! [[ "$octoVersion" =~ ^1\.[89].* ]]; then | |
| echo "liboctomap-dev is only available in version $octoVersion but we need at least version 1.8.0." >&2 | |
| versionError=true | |
| fi | |
| if $versionError; then | |
| echo "You can install the following packages manually and restart the script:" | |
| echo " http://mirrors.kernel.org/ubuntu/pool/universe/f/fcl/libfcl0.5_0.5.0-5_amd64.deb" | |
| echo " http://mirrors.kernel.org/ubuntu/pool/universe/f/fcl/libfcl-dev_0.5.0-5_amd64.deb" | |
| echo " http://mirrors.kernel.org/ubuntu/pool/universe/o/octomap/liboctomap1.8_1.8.1+dfsg-1_amd64.deb" | |
| echo " http://mirrors.kernel.org/ubuntu/pool/universe/o/octomap/liboctomap-dev_1.8.1+dfsg-1_amd64.deb" | |
| echo "" | |
| echo "Example:" | |
| echo " wget http://mirrors.kernel.org/ubuntu/pool/universe/f/fcl/libfcl0.5_0.5.0-5_amd64.deb" | |
| echo " sudo dpkg -i libfcl0.5_0.5.0-5_amd64.deb" | |
| exit 1 | |
| fi | |
| cd "$installPath" | |
| if ! [ -d "pifuhd" ]; then | |
| git clone https://github.com/facebookresearch/pifuhd.git || exit 1 | |
| fi | |
| cd pifuhd | |
| if ! [ -f "checkpoints/pifuhd.pt" ]; then | |
| sh ./scripts/download_trained_model.sh | |
| fi | |
| if ! [ -d ".venv" ]; then | |
| python3 -m venv .venv | |
| fi | |
| source .venv/bin/activate | |
| pip install --upgrade pip || exit 1 | |
| pip install numpy || exit 1 | |
| pip install torch==1.4.0+cpu torchvision==0.5.0+cpu -f https://download.pytorch.org/whl/torch_stable.html || exit 1 | |
| pip install wheel || exit 1 | |
| pip install opencv-python tqdm matplotlib scikit-image pyopengl trimesh[all] pycocotools || exit 1 | |
| mkdir -p content | |
| cd content | |
| if ! [ -d "lightweight-human-pose-estimation.pytorch" ]; then | |
| git clone https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch.git | |
| fi | |
| cd lightweight-human-pose-estimation.pytorch | |
| wget -nc https://download.01.org/opencv/openvino_training_extensions/models/human_pose_estimation/checkpoint_iter_370000.pth | |
| cat > "getrect.py" << EOM | |
| import torch | |
| import cv2 | |
| import numpy as np | |
| from models.with_mobilenet import PoseEstimationWithMobileNet | |
| from modules.keypoints import extract_keypoints, group_keypoints | |
| from modules.load_state import load_state | |
| from modules.pose import Pose, track_poses | |
| import demo | |
| import argparse | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('-i', '--image_path', type=str, default=None) | |
| args = parser.parse_args() | |
| def get_rect(net, images, height_size, cpu=False): | |
| net = net.eval() | |
| stride = 8 | |
| upsample_ratio = 4 | |
| num_keypoints = Pose.num_kpts | |
| previous_poses = [] | |
| delay = 33 | |
| for image in images: | |
| rect_path = image.replace('.%s' % (image.split('.')[-1]), '_rect.txt') | |
| img = cv2.imread(image, cv2.IMREAD_COLOR) | |
| orig_img = img.copy() | |
| orig_img = img.copy() | |
| heatmaps, pafs, scale, pad = demo.infer_fast(net, img, height_size, stride, upsample_ratio, cpu=cpu) | |
| total_keypoints_num = 0 | |
| all_keypoints_by_type = [] | |
| for kpt_idx in range(num_keypoints): # 19th for bg | |
| total_keypoints_num += extract_keypoints(heatmaps[:, :, kpt_idx], all_keypoints_by_type, total_keypoints_num) | |
| pose_entries, all_keypoints = group_keypoints(all_keypoints_by_type, pafs, demo=True) | |
| for kpt_id in range(all_keypoints.shape[0]): | |
| all_keypoints[kpt_id, 0] = (all_keypoints[kpt_id, 0] * stride / upsample_ratio - pad[1]) / scale | |
| all_keypoints[kpt_id, 1] = (all_keypoints[kpt_id, 1] * stride / upsample_ratio - pad[0]) / scale | |
| current_poses = [] | |
| rects = [] | |
| for n in range(len(pose_entries)): | |
| if len(pose_entries[n]) == 0: | |
| continue | |
| pose_keypoints = np.ones((num_keypoints, 2), dtype=np.int32) * -1 | |
| valid_keypoints = [] | |
| for kpt_id in range(num_keypoints): | |
| if pose_entries[n][kpt_id] != -1.0: # keypoint was found | |
| pose_keypoints[kpt_id, 0] = int(all_keypoints[int(pose_entries[n][kpt_id]), 0]) | |
| pose_keypoints[kpt_id, 1] = int(all_keypoints[int(pose_entries[n][kpt_id]), 1]) | |
| valid_keypoints.append([pose_keypoints[kpt_id, 0], pose_keypoints[kpt_id, 1]]) | |
| valid_keypoints = np.array(valid_keypoints) | |
| if pose_entries[n][10] != -1.0 or pose_entries[n][13] != -1.0: | |
| pmin = valid_keypoints.min(0) | |
| pmax = valid_keypoints.max(0) | |
| center = (0.5 * (pmax[:2] + pmin[:2])).astype(np.int) | |
| radius = int(0.65 * max(pmax[0]-pmin[0], pmax[1]-pmin[1])) | |
| elif pose_entries[n][10] == -1.0 and pose_entries[n][13] == -1.0 and pose_entries[n][8] != -1.0 and pose_entries[n][11] != -1.0: | |
| # if leg is missing, use pelvis to get cropping | |
| center = (0.5 * (pose_keypoints[8] + pose_keypoints[11])).astype(np.int) | |
| radius = int(1.45*np.sqrt(((center[None,:] - valid_keypoints)**2).sum(1)).max(0)) | |
| center[1] += int(0.05*radius) | |
| else: | |
| center = np.array([img.shape[1]//2,img.shape[0]//2]) | |
| radius = max(img.shape[1]//2,img.shape[0]//2) | |
| x1 = center[0] - radius | |
| y1 = center[1] - radius | |
| rects.append([x1, y1, 2*radius, 2*radius]) | |
| np.savetxt(rect_path, np.array(rects), fmt='%d') | |
| net = PoseEstimationWithMobileNet() | |
| checkpoint = torch.load('checkpoint_iter_370000.pth', map_location=torch.device('cpu')) | |
| load_state(net, checkpoint) | |
| get_rect(net.cpu(), [args.image_path], 512, cpu = True) | |
| EOM | |
| cd "${installPath}/pifuhd" | |
| git apply - 2>/dev/null << EOM | |
| diff --git a/apps/recon.py b/apps/recon.py | |
| index 8b2c98f..a5f75f3 100644 | |
| --- a/apps/recon.py | |
| +++ b/apps/recon.py | |
| @@ -145,7 +145,7 @@ def recon(opt, use_rect=False): | |
| state_dict = None | |
| if state_dict_path is not None and os.path.exists(state_dict_path): | |
| print('Resuming from ', state_dict_path) | |
| - state_dict = torch.load(state_dict_path) | |
| + state_dict = torch.load(state_dict_path, map_location=torch.device('cpu')) | |
| print('Warning: opt is overwritten.') | |
| dataroot = opt.dataroot | |
| resolution = opt.resolution | |
| @@ -162,7 +162,7 @@ def recon(opt, use_rect=False): | |
| # parser.print_options(opt) | |
| - cuda = torch.device('cuda:%d' % opt.gpu_id) | |
| + cuda = torch.device('cpu') | |
| if use_rect: | |
| test_dataset = EvalDataset(opt) | |
| EOM | |
| cat >> ".gitignore" << EOM | |
| content/ | |
| .vscode/ | |
| .venv/ | |
| *.pyc | |
| results/ | |
| checkpoints/ | |
| EOM | |
| cat > "run.sh" << EOM | |
| #!/bin/bash | |
| if [ -z "\$1" ]; then | |
| echo "Missing parameter: $0 <image>" >&2 | |
| exit 1 | |
| fi | |
| image="\$(realpath "\$1")" | |
| dirImage="\$(dirname "\$image")" | |
| source .venv/bin/activate | |
| cd content/lightweight-human-pose-estimation.pytorch | |
| python getrect.py -i "\$image" | |
| cd ../.. | |
| python -m apps.simple_test -r 256 --use_rect -i "\$dirImage" | |
| EOM | |
| chmod +x run.sh | |
| mv samples_images/test_keypoints.json{,.bak} 2>/dev/null | |
| echo "You can now go to ${installPath}/pifuhd/ and execute" | |
| echo " run.sh samples_images/test.png" | |
| echo "to check if it is working correctly." | |
| echo "" | |
| echo "Change the value in the last line in 'run.sh' to 512 if you have enough memory." | |
| echo "You can find the results in results/pifuhd_final/recon/" |
thanks dude
i have some issue (im not good at ai/ml stuffs) , so as per my case im using an ubuntu 20 server with 16 gigs of ram and activated the virtual environment manually and all the packages are install properly though i think something is messed :)
Author
i have some issue (im not good at ai/ml stuffs) , so as per my case im using an ubuntu 20 server with 16 gigs of ram and activated the virtual environment manually and all the packages are install properly though i think something is messed :)
Unfortunately I am also not experienced in AI stuff. I was only able to get it installed properly. I didn't use this script since I created it. But it seems that the human pose estimation got an update and the parameter demo is no longer used as you can see here: https://github.com/Daniil-Osokin/lightweight-human-pose-estimation.pytorch/blob/1590929b601535def07ead5522f05e5096c1b6ac/modules/keypoints.py#L64
It was changed already 3 years ago in this commit: Daniil-Osokin/lightweight-human-pose-estimation.pytorch@ee9e4cc
So if you are lucky you can just delete the demo=True parameter in getrect.py on line 30 and try again.
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thanks that very useful!