From d41328b5100c68ebcdf31721385ca68b320bbacf Mon Sep 17 00:00:00 2001 From: Yixing Lao Date: Tue, 13 Oct 2020 06:18:40 -0700 Subject: [PATCH] initial commit --- .gitignore | 2 + assets/open3d_vis.png | Bin 0 -> 123032 bytes categories.json | 9773 +++++++++++++++++++++++++++++++++++ meshes.json | 443 ++ readme.md | 140 + redwood_3dscan.py | 160 + rgbds.json | 10935 ++++++++++++++++++++++++++++++++++++++++ test.py | 7 + 8 files changed, 21460 insertions(+) create mode 100644 .gitignore create mode 100644 assets/open3d_vis.png create mode 100644 categories.json create mode 100644 meshes.json create mode 100644 readme.md create mode 100644 redwood_3dscan.py create mode 100644 rgbds.json create mode 100644 test.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..9202c09 --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +data/ +__pycache__/ diff --git a/assets/open3d_vis.png b/assets/open3d_vis.png new file mode 100644 index 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"09398", + "09400", + "09412", + "09413", + "09418", + "09420", + "09422", + "09452", + "09453", + "09454", + "09472", + "09487", + "09515", + "09518", + "09606", + "09608", + "09615", + "09620", + "09622", + "09625", + "09637", + "09639", + "09640", + "09643", + "09647", + "09648", + "09659", + "09666", + "09669", + "09690", + "09692", + "09862", + "09864", + "09865", + "09867", + "09868", + "09936", + "09937", + "10007", + "10009", + "10116", + "10350", + "10544", + "10546", + "10548", + "10664" +] \ No newline at end of file diff --git a/readme.md b/readme.md new file mode 100644 index 0000000..205c14a --- /dev/null +++ b/readme.md @@ -0,0 +1,140 @@ +# A Large Dataset of Object Scans (redwood-3dscan) + +

+ +

+ +## Abstract + +We have created a dataset of more than ten thousand 3D scans of real objects. +To create the dataset, we recruited 70 operators, equipped them with +consumer-grade mobile 3D scanning setups, and paid them to scan objects in +their environments. The operators scanned objects of their choosing, outside the +laboratory and without direct supervision by computer vision professionals. The +result is a large and diverse collection of object scans: from shoes, mugs, and +toys to grand pianos, construction vehicles, and large outdoor sculptures. We +worked with an attorney to ensure that data acquisition did not violate privacy +constraints. The acquired data was irrevocably placed in the public domain and +is available freely. + +You can preview and explore the dataset at +[http://redwood-data.org/3dscan/](http://redwood-data.org/3dscan/). + +## Dataset organization + +If you use our download scripts, the downloaded dataset will be stored in `data/`. + +```txt +data +├── rgbd (10,933 RGBD scans, each contains multiple RGB and depth images) +│   ├── 00001.zip +│   ├── 00002.zip +│   ├── ... +│   ├── 11097.zip +│   └── 11098.zip +├── mesh (441 reconstructed models) +│   ├── 00004.ply +│   ├── 00033.ply +│   ├── ... +│   ├── 10548.ply +│   └── 10664.ply +└── video (10,933 videos created from images) + ├── 00001.mp4 + ├── 00002.mp4 + ├── ... + ├── 11097.mp4 + └── 11098.mp4 +``` + +- Dataset size: The entire dataset is ~4TB in size. +- RGBD scans: There are 10,933 RGBD scans. Each scan contains multiple RGBD images. +- Meshes: There are 441 reconstructed mesh models. +- Videos: There are 10,933 videos, created from RGBD images. +- Categories: 9,131 RGBD scans are categorized into 320 categories. Each scan has at most one category. + +## Example usage + +```python +import redwood_3dscan as rws + +# Print RGBD scans (list) +print(rws.rgbds) + +# Print meshes (list) +print(rws.meshes) + +# Print categories (dict: string->list) +print(rws.categories) + +# Print all scan_id of the "sofa" category +print(rws.categories["sofa"]) + +# Download by scan_id "00033" +# Download will be skipped if the resource is unavailable +# e.g. some RGBD images may not come with mesh. +rws.download_rgbd("00033") # Save to data/rgbd/00033.zip, if available +rws.download_mesh("00033") # Save to data/mesh/00033.ply, if available +rws.download_video("00033") # Save to data/video/00033.mp4, if available +rws.download_all("00033") # Downloads rgbd, mesh, and video together + +# Download by category "sofa" +rws.download_category("sofa") + +# Download the entire dataset +# WARNING: the dataset is ~4TB in size +for scan_id in rws.rgbds: + rws.download_all(scan_id) +``` + +You can use +[Open3D](https://github.com/intel-isl/Open3D) to load and visualize the models. + +```shell +# For installation guides, see: +# http://www.open3d.org/docs/release/getting_started.html +pip install open3d +``` + +```python +import redwood_3dscan as rws +import open3d as o3d + +rws.download_mesh("00033") +mesh = o3d.io.read_triangle_mesh("data/mesh/00033.ply") +mesh.compute_vertex_normals() +o3d.visualization.draw_geometries([mesh]) +``` + +![Open3D Visualizer](assets/open3d_vis.png) + +## License + +The entire dataset, including both RGB-D scans and reconstructed models, is in +the [public domain](https://wiki.creativecommons.org/wiki/Public_domain). Any +part of the dataset can be used for any purpose with proper attribution. If +you use any of the data, please cite +[our technical report](http://arxiv.org/abs/1602.02481). + +```bibtex +@article{Choi2016, + author = {Sungjoon Choi and Qian-Yi Zhou and Stephen Miller and Vladlen Koltun}, + title = {A Large Dataset of Object Scans}, + journal = {arXiv:1602.02481}, + year = {2016}, + } +``` + +## File Format + +The RGB-D sequences were acquired with PrimeSense Carmine cameras. The +resolution is 640×480, the frame rate is 30Hz. Each scan is packaged in a zip +archive that contains consecutive color images stored as JPG and depth images +stored as 16-bit PNG, where pixel values represent depth in millimeters. The +first part of a file name indicates the frame number and the second part +provides a time stamp in microseconds. + +The focal length is 525 for both axes and the principal point is (319.5, 239.5). +The depth images are registered to the color images. + +The reconstructed models are all in +[PLY file format](https://en.wikipedia.org/wiki/PLY_(file_format)). diff --git a/redwood_3dscan.py b/redwood_3dscan.py new file mode 100644 index 0000000..93eeacf --- /dev/null +++ b/redwood_3dscan.py @@ -0,0 +1,160 @@ +######################################################## +# Python script for downloading "A Large Dataset of Object Scans" dataset. +# +# Requirements: +# - Python 2.7 or 3.x +# - This script requires 'requests' module +# +# For more details, visit: +# - https://github.com/intel-isl/redwood-3dscan +# - http://redwood-data.org/3dscan +######################################################## + +import json +import requests +import time +import os +import sys + + +def _load_json(file_name): + with open(file_name, 'r') as f: + return json.load(f) + + +def _download(url, dst_file, skip_if_exists=True): + print("Downloading {} to {}.".format(url, dst_file)) + + if skip_if_exists and os.path.isfile(dst_file): + print("{} already exists. Skipped.".format(dst_file)) + return True + + dst_dir = os.path.dirname(dst_file) + if not os.path.exists(dst_dir): + print("Creating directory {}".format(dst_dir)) + os.makedirs(dst_dir) + + start_time = time.time() + try: + r = requests.get(url, stream=True) + if r.ok: + num_bytes = 0 + with open(dst_file, 'wb') as f: + for chunk in r.iter_content(32768): + num_bytes += len(chunk) + f.write(chunk) + mbytes = num_bytes / float(1000000) + elapsed_time = time.time() - start_time + speed = mbytes / elapsed_time + print("Downloaded {:.2f}MB, speed {:.2f}MB/s.".format( + mbytes, speed)) + return True + else: + print("Download request failed.") + return False + except: + e = sys.exc_info()[0] + print("Download request failed with exception {}.".format(e)) + return False + + +# List of RGBD image ids. +rgbds = _load_json("rgbds.json") + +# List of mesh ids. +meshes = _load_json("meshes.json") + +# Dictionary with {"category_0": [id_0, id_1, ...]}. +categories = _load_json("categories.json") + +_base_url = "https://s3.us-west-1.wasabisys.com/redwood-3dscan" +_pwd = os.path.dirname(os.path.abspath(__file__)) + + +def download_rgbd(scan_id, skip_if_exists=True): + """Download RGBD scan by scan_id. + + Downloaded file will be saved to "data/rgbd/{scan_id}.zip". + + Args: + scan_id: String of 5 digits, e.g. "00072". + skip_if_exists: Skip downloading if the file already exists. + """ + if scan_id in rgbds: + url = "{}/rgbd/{}.zip".format(_base_url, scan_id) + dst_file = os.path.join(_pwd, "data", "rgbd", "{}.zip".format(scan_id)) + _download(url, dst_file, skip_if_exists=skip_if_exists) + else: + print("RGBD scan_id {} is not available. Skipped.".format(scan_id)) + + +def download_mesh(scan_id, skip_if_exists=True): + """Download reconstructed mesh by scan_id. + + Downloaded file will be saved to "data/mesh/{scan_id}.zip". + + Args: + scan_id: String of 5 digits, e.g. "00072". + skip_if_exists: Skip downloading if the file already exists. + """ + if scan_id in meshes: + url = "{}/mesh/{}.ply".format(_base_url, scan_id) + dst_file = os.path.join(_pwd, "data", "mesh", "{}.ply".format(scan_id)) + _download(url, dst_file, skip_if_exists=skip_if_exists) + else: + print("Mesh scan_id {} is not available. Skipped.".format(scan_id)) + + +def download_video(scan_id, skip_if_exists=True): + """Download RGB video by scan_id. + + Downloaded file will be saved to "data/video/{scan_id}.zip". + + Args: + scan_id: String of 5 digits, e.g. "00072". + skip_if_exists: Skip downloading if the file already exists. + """ + if scan_id in rgbds: + url = "{}/video/{}.mp4".format(_base_url, scan_id) + dst_file = os.path.join(_pwd, "data", "video", + "{}.mp4".format(scan_id)) + _download(url, dst_file, skip_if_exists=skip_if_exists) + else: + print("Video scan_id {} is not available. Skipped.".format(scan_id)) + + +def download_all(scan_id, skip_if_exists=True): + """Download RGBD images, mesh and video by scan_id, if available. + + Downloaded file will be saved to "data/". + + Args: + scan_id: String of 5 digits, e.g. "00072". + skip_if_exists: Skip downloading if the file already exists. + """ + download_rgbd(scan_id, skip_if_exists=skip_if_exists) + download_mesh(scan_id, skip_if_exists=skip_if_exists) + download_video(scan_id, skip_if_exists=skip_if_exists) + + +def download_category(category_name, skip_if_exists=True): + """Download RGBD images, mesh and video by category_name, if available. + + Downloaded file will be saved to "data/". + + Args: + category_name: String of the category name, e.g. "sofa". + skip_if_exists: Skip downloading if the file already exists. + """ + print("Downloading category {}.".format(category_name)) + if category_name not in categories: + print("Category {} not found. Skipped.".format(category_name)) + else: + for scan_id in categories[category_name]: + download_all(scan_id, skip_if_exists=skip_if_exists) + + +if __name__ == "__main__": + # Test cases + download_all("00001") + download_category("atm") diff --git a/rgbds.json b/rgbds.json new file mode 100644 index 0000000..2183810 --- /dev/null +++ b/rgbds.json @@ -0,0 +1,10935 @@ +[ + "00001", + "00002", + "00003", + "00004", + "00005", + "00006", + "00007", + "00008", + "00009", + "00010", + "00011", + "00012", + "00013", + "00014", + "00015", + "00016", + "00017", + "00018", + "00019", + "00020", + "00021", + "00022", + "00023", + "00024", + "00025", + "00026", + "00027", + "00028", + "00029", + "00030", + "00031", + "00032", + "00033", + "00034", + "00035", + "00036", + "00037", + "00038", + "00039", + "00040", + "00041", + "00042", + "00043", + "00044", + "00045", + "00046", + "00047", + "00048", + "00049", + "00050", + "00051", + "00052", + "00053", + "00054", + "00055", + "00056", + "00057", 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