Detic
YOLOX
Detic | YOLOX | |
---|---|---|
11 | 12 | |
1,769 | 9,030 | |
1.0% | 1.0% | |
1.9 | 1.0 | |
about 1 month ago | 3 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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Detic
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Autodistill: A new way to create CV models
Some of the foundation/base models include: * GroundedSAM (Segment Anything Model) * DETIC * GroundingDINO
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[P] Image search with localization and open-vocabulary reranking.
For localisation at search time I ended up using OWL-ViT. This worked really well. I did not try Detic or CLIPseg but would be interested to hear if anyone else has tried these?
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training object detector using classified images?
git clone https://github.com/facebookresearch/Detic cd Detic pip install -r requirements python demo.py --config-file configs/Detic_LCOCOI21k_CLIP_SwinB_896b32_4x_ft4x_max-size.yaml --input desk.jpg --output out.jpg --vocabulary lvis --opts MODEL.WEIGHTS models/Detic_LCOCOI21k_CLIP_SwinB_896b32_4x_ft4x_max-size.pth
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[P] Any object detection library
You might want to take a look at DETIC : https://github.com/facebookresearch/Detic (Open Vocabulary Object Detection, trained on thousands of classes)
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[P] Awesome Image Segmentation Project Based on Deep Learning (5.6k star)
Are there any open-label segmentation model included in this repo, like Detic or LSeg?
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[R] CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory + Code + Robot demo
We made this using pretty recent advances in web-data pretrained models like Detic and LSeg for detection, CLIP for visual queries, and Sentence BERT for semantic queries. Our "database" is really a neural field (Instant NGP) that maps from 3D coordinates to a high dimensional embedding vector in the same representation space as CLIP and SBERT.
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[P] Using OpenAI's CLIP repository as a support, I was able to create a software to detect anything in an image at its original resolution!
Is it similar to the open vocabulary detic?
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Researchers at Meta and the University of Texas at Austin Propose βDeticβ: A Method to Detect Twenty-Thousand Classes using Image-Level Supervision
Code for https://arxiv.org/abs/2201.02605 found: https://github.com/facebookresearch/Detic
- Detecting Twenty-thousand Classes using Image-level Supervision
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[R] Detecting Twenty-thousand Classes using Image-level Supervision
github: https://github.com/facebookresearch/Detic
YOLOX
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Learning Exchange, lets training YoloX
So I am trying to do my best and train YOLOX for an object detection case using Google Colab.
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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
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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
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[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.
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DeepSort with PyTorch(support yolo series)
Megvii-BaseDetection/YOLOX
- [D][P] YOLOv6: state-of-the-art object detection at 1242 FPS
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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
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High-tech
Not really a problem, see results here. Just use yolox_x. Thank you for your attention.
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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?
GroundingDINO - Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
ultralytics - NEW - YOLOv8 π in PyTorch > ONNX > OpenVINO > CoreML > TFLite
tensorrt_demos - TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
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.
clipseg - This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
yolov5 - YOLOv5 π in PyTorch > ONNX > CoreML > TFLite
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
RPi_64-bit_Zero-2-image - Raspberry Pi Zero 2 W 64-bit OS image with OpenCV, TensorFlow Lite and ncnn Framework.