odam
yolov7
| odam | yolov7 | |
|---|---|---|
| 2 | 33 | |
| 31 | 12,739 | |
| - | - | |
| 0.0 | 3.2 | |
| 10 months ago | 8 days ago | |
| Go | Jupyter Notebook | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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odam
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GoCV vs OpenCV Python Performance
Yeah, I tried to use GoCV in my pet project for object detection: https://github.com/LdDl/odam. It fits all my current needs (since I know how to port some python/c++ techniques for computer vision) The only thing I'm really struggling about is there is no straightforward simple way to make GPU-build it for Windows (as far as I know).
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Go Object Detection Package (YOLO V3)
I'm working on similar project (yolov4): https://github.com/LdDl/odam But, I'm using gocv.Mat -> darknet-based image (go darknet bindings) conversion.
yolov7
- FLaNK Stack Weekly 16 October 2023
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Train a ML model able to identify animal species
If you want something off-the-shelf, try YoloV7.
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A video based Latin dictionary: get what you see in Latin (beta) - What do you think?
The current dictionary is still in a beta state and has only been trained on 80 words (e.g. 'man', 'dog', 'car', 'keyboard', 'book', etc.; see list of words, see dataset). I used the object detection model Yolov7 (paper, all credits to them).
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
(Please note, this is a re-post of my original question here, I think this subreddit might be more appropriate for asking this question)At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be the exact same model as the company does have pre-trained weights for this exact model). However, Unity only supports ONNX so I exported the model as an ONNX model, using the code provided in the repo:
- Coding Question Help
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DL for the Web: Repository of Models
Github Projects offering pretrained weights and train / run scripts. Example
- [OC] Football Player 3D Pose Estimation using YOLOv7 and Matplotlib
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Finding a good Tiny Yolo to train in Python
The only project I found is this one that implements Yolov7
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Visualizing image augmentations from YOLOV7
I'm wondering if there's an efficient way to visualize the image augmentations from the Yolov7 hyperparameters list here
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Train YOLOv8 ObjectDetection on Custom Dataset Tutorial
yolov7: https://github.com/WongKinYiu/yolov7#performance
What are some alternatives?
gocv - Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, and OpenCV Contrib.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
awesome-tiny-object-detection - 🕶 A curated list of Tiny Object Detection papers and related resources.
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
darknet - Convolutional Neural Networks
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
CATNet - 🛰️ Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images (TNNLS 2023)