VISYM COLLECTOR
-------------------
[![PyPI version](https://badge.fury.io/py/pycollector.svg)](https://badge.fury.io/py/pycollector) [![pycollector unit tests](https://github.com/visym/collector/workflows/pycollector%20unit%20tests/badge.svg)](https://github.com/visym/collector/actions?query=workflow%3A%22pycollector+unit+tests%22)
Live Datasets for Visual AI
URL: https://github.com/visym/collector/
Datasets: https://visym.github.io/collector/
[Visym Collector](https://visym.com/collector) is a global platform for collecting large scale consented video datasets of people for visual AI applications. Collector is able to record, annotate and verify custom video datasets of rarely occuring activities for training visual AI systems, at an order of magnitude lower cost than existing methods. Our distributed data collection team is spread over five continents and fifty countries to collect unbiased datasets for global visual AI applications.
Visym Collector provides:
* On-demand collection of rare classes
* Simultaneous video recording, annotation and verification into a single unified platform
* Touchscreen UI for live annotation of bounding boxes, activity clips and object categories
* Consented videos of people for ethical dataset construction with in-app face anonymization
* Python tools for hard negative mining and live model testing in PyTorch
Requirements
-------------------
python 3.*
[ffmpeg](https://ffmpeg.org/download.html) (required for videos)
[vipy](https://github.com/visym/vipy), torch, boto3, pandas
Installation
-------------------
```python
pip install pycollector
```
Quickstart
-------------------
<a href="https://visym.com/collector"><img alt="iOS" src="https://developer.apple.com/app-store/marketing/guidelines/images/badge-download-on-the-app-store.svg" height="50"/></a> <a href="https://visym.com/collector"><img alt="Android" src="https://upload.wikimedia.org/wikipedia/commons/7/78/Google_Play_Store_badge_EN.svg" height="50"/></a>
* **Install.** Get the Visym Collector app (contact us to join the private beta!) and sign-up as a new user.
* **Collect.** Collect a labeled video using the mobile app, then retrieve and visualize it using the python tools:
```python
import pycollector.video
v = pycollector.video.last().show()
```
* **Test.** Convert to a 64x3x224x224 PyTorch tensor for testing with your network:
```python
t = v.clip(0,64).activitytube(maxdim=224).torch()
```
* **Repeat.** Collect more videos like those your network got wrong, or let our collection team collect for you!
The [demos](https://github.com/visym/collector/tree/master/demo) will provide additional useful tutorials to help you get started.
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资源分类:Python库 所属语言:Python 资源全名:visym-collector-0.0.55.tar.gz 资源来源:官方 安装方法:https://lanzao.blog.csdn.net/article/details/101784059
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visym-collector-0.0.55.tar.gz (82个子文件)
visym-collector-0.0.55
MANIFEST.in 103B
PKG-INFO 633B
setup_common.py 1KB
setup_alias.py 924B
test
test_detection.py 5KB
test_pycollector_API.py 2KB
test_backend.py 313B
test_get_project.py 854B
test_user_management.py 576B
test_import.py 462B
LICENSE 34KB
visym_collector.egg-info
PKG-INFO 633B
requires.txt 87B
SOURCES.txt 3KB
top_level.txt 12B
namespace_packages.txt 12B
dependency_links.txt 1B
setup.cfg 38B
setup.py 920B
README.md 3KB
pycollector
video.py 27KB
globals.py 3KB
user.py 7KB
project.py 4KB
model
yolov5
models
common.py 7KB
yolo.py 12KB
yolov5s.yaml 1KB
__init__.py 0B
yolov5x.yaml 1KB
yolov5l.yaml 1KB
export.py 4KB
yolov5m.yaml 1KB
experimental.py 6KB
coco.names 625B
__init__.py 0B
utils
loss.py 8KB
metrics.py 8KB
general.py 18KB
activations.py 2KB
autoanchor.py 7KB
torch_utils.py 9KB
__init__.py 0B
google_utils.py 5KB
pyvideoresearch
__init__.py 0B
bases
resnet50_3d.py 6KB
resnet50_3d_decoder2.py 6KB
resnet50_3d_nonlocal_noinit.py 2KB
resnet50_3d_encoder3.py 1KB
resnet50_3d_nonlocal.py 2KB
resnet50_3d_decoder.py 6KB
resnet50_3d_autoencoder.py 1KB
__init__.py 0B
resnet50_3d_encoder.py 1KB
resnet50_3d_decoder4.py 6KB
resnet50_3d_nonlocal_nobn.py 2KB
resnet50_3d_decoder3.py 6KB
resnet50_3d_autoencoder4.py 1KB
mock_base.py 174B
resnet50_3d_autoencoder3.py 1KB
resnet101_3d.py 711B
base.py 199B
face
recognition.py 8KB
__init__.py 0B
faster_rcnn.py 81KB
detection.py 24KB
ResNets_3D_PyTorch
resnet.py 7KB
__init__.py 0B
__init__.py 0B
yolov3
coco.names 625B
__init__.py 0B
utils
utils.py 12KB
__init__.py 0B
parse_config.py 1KB
network.py 15KB
dataset.py 53KB
label.py 28KB
util.py 4KB
recognition.py 37KB
__init__.py 56B
backend.py 3KB
version.py 577B
detection.py 32KB
共 82 条
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