optical.flow.demo
caer
| optical.flow.demo | caer | |
|---|---|---|
| 7 | 8 | |
| 549 | 749 | |
| - | - | |
| 4.3 | 0.0 | |
| over 2 years ago | 7 months ago | |
| Python | Python | |
| Mozilla Public License 2.0 | MIT License |
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optical.flow.demo
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Just another reason why this game should of been a paid multiplayer/campaign
we all need to support this application that is being developed: https://www.waldo.vision/
- With enough data and support, Waldo anti-cheat seems like a viable solution to cheaters (past, present, future)
- Waldo: Visually detecting hacking or cheating in videos from FPS games
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We Can Save FPS Games - Using machine learning to spot cheating in gameplay footage
What is WALDO?
caer
- Show HN: Caer – A lightweight GPU-accelerated Vision library in Python
- I wrote a lightweight GPU-accelerated Vision library in Python
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Jetson nano python3 illegal instruction problem
I think it may have. If you look at line 10 of https://github.com/jasmcaus/caer/blob/master/configs.ini, you’ll see that caer has numpy and opencv-contrib-python dependencies that get referenced in its setup.py. If I recall correctly, pip on the nano doesn’t pick up the default numpy and opencv-python system installs, so when you go to install something like caer that has them as dependencies, it will install new copies except the wheel files that it grabs are incompatible. The solution I have found to work is to run something similar to the command above: “pip3 install —no-binary caer —no-binary numpy—no-binary opencv-contrib-python —no-binary typing-extensions —no-binary mypy —force-reinstall caer”. Some of those —no-binary options may not be necessary but they’ll at least ensure pip grabs the source for each of the dependencies and rebuilds it locally rather than using an imcompatible version. This command will take awhile! But you only should have to do it once.
- jasmcaus/caer Modern Computer Vision on the Fly
- Caer: High-performance Vision Library in Python (faster than Torchvision)
- Caer – A GPU-accelerated Computer Vision library (faster than Torchvision)
- jasmcaus/caer lightweight, scalable Computer Vision library for high-performance AI research
- Caer – A GPU-Accelerated Computer Vision Library in Python
What are some alternatives?
frame-interpolation - FILM: Frame Interpolation for Large Motion, In ECCV 2022.
fiftyone - The open-source tool for building high-quality datasets and computer vision models
VQGAN-CLIP-Video - Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.
img2table - img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
yolov7-pose-estimation - YOLOv7 Pose estimation using OpenCV, PyTorch
opencv - Haskell binding to OpenCV-3.x
opencv-steel-darts - Automatic scoring system for steel darts using OpenCV, a Raspberry Pi 3 Model B and two webcams.
Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
unimatch - [TPAMI'23] Unifying Flow, Stereo and Depth Estimation
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
moviepy - Video editing with Python
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!