ComfyUI-Depth-Anything-Tensorrt
YOLOX
| ComfyUI-Depth-Anything-Tensorrt | YOLOX | |
|---|---|---|
| 2 | 12 | |
| 58 | 9,115 | |
| - | 1.1% | |
| 7.7 | 0.0 | |
| 1 day ago | 3 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ComfyUI-Depth-Anything-Tensorrt
YOLOX
-
Learning Exchange, lets training YoloX
So I am trying to do my best and train YOLOX for an object detection case using Google Colab.
-
Understanding heatmaps
https://github.com/Megvii-BaseDetection/YOLOX I have only tried the pretrained yolo X nano. I get corner responses even if the inference image is padded with a large margin which is unexpected
-
Open discussion and useful links people trying to do Object Detection
* Nice implemention of Yolo that is BSD license (not GPL) https://github.com/Megvii-BaseDetection/YOLOX
-
[P] Image search with localization and open-vocabulary reranking.
I wanted to have a few choices getting localization into image search (index and search time). I immediately thought of using a region proposal network (rpn) from mask-rcnn to create patches that can also be indexed and searched (and add the localisation). I figured it might be somewhat agnostic to classes. I did not want to use mmdetection or detectron2 due to their dependencies and just getting the rpn was not worth it. I was encouraged by the PyTorch native implementations of detection/segmentation models but ended up finding yolox the best.
-
DeepSort with PyTorch(support yolo series)
Megvii-BaseDetection/YOLOX
- [D][P] YOLOv6: state-of-the-art object detection at 1242 FPS
-
Looking for help for hire
Modern video can be broken into a series of still problems. AI vision models can make these types of classification in as fast as video. Here is a particularly there is a controversial company from China that does this very well on faces in video and they have open sourced the models: https://github.com/Megvii-BaseDetection/YOLOX
-
High-tech
Not really a problem, see results here. Just use yolox_x. Thank you for your attention.
-
Advice on Masters project | Vision transformers
From what I understand the swin transformer outputs a single dimension feature vector and the yolo head takes inputs from 3 different layers from the backbone?? and I think I will need to write the backbone implementation here.
- Is YOLOX object detector NMS free?
What are some alternatives?
ComfyUI-IDM-VTON - ComfyUI adaptation of IDM-VTON for virtual try-on.
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
tensorrt_demos - TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
RPi_64-bit_Zero-2-image - Raspberry Pi Zero 2 W 64-bit OS image with OpenCV, TensorFlow Lite and ncnn Framework.
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
tflite2tensorflow - Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.
TACO - 🌮 Trash Annotations in Context Dataset Toolkit
opti_models - PyTorch optimizations and benchmarking
tensorRT_Pro - C++ library based on tensorrt integration