1.ultralytics / yolov5
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
+653 stars
from 57,594 · score 6.48
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2.onnx / onnx
Open standard for machine learning interoperability
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from 21,208 · score 6.06
3.Megvii-BaseDetection / YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
+145 stars
from 10,539 · score 4.98
4.llmware-ai / llmware
Unified framework for building enterprise RAG pipelines with small, specialized models
+72 stars
from 14,746 · score 4.29
5.ultralytics / yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
+65 stars
from 10,566 · score 4.19
6.jina-ai / clip-as-service
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
+13 stars
from 12,819 · score 2.64
7.microsoft / MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
+9 stars
from 5,795 · score 2.30
8.gmalivenko / pytorch2keras
PyTorch to Keras model convertor
+1 stars
from 860 · score 0.69