tf-glow-tts
yolov4-custom-functions
| tf-glow-tts | yolov4-custom-functions | |
|---|---|---|
| 1 | 3 | |
| 6 | 596 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | over 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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tf-glow-tts
yolov4-custom-functions
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How can i count Enter and Exit in Yolov Object Detection?
Object detection and counting project: https://github.com/theAIGuysCode/yolov4-custom-functions
- Contagem de motocicletas no evento do Bozo em SP. Total: 6253.
- Contagem em tempo real das motos durante a motocada promovida pelo presidente Bolsonaro (contagem final: 6253)
What are some alternatives?
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yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
Swin-Transformer-Tensorflow - Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
mousehunter-edge - Cat with prey detection on Raspberry Pi. Lock cat pet flap if prey is detected. Object detection implemented in TFLite with ImageNet v1 SSD. Inference on EdgeTPU (Google Coral USB). Stores images on AWS S3 and sends notifications to iOS device.
edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.
CFU-Playground - Want a faster ML processor? Do it yourself! -- A framework for playing with custom opcodes to accelerate TensorFlow Lite for Microcontrollers (TFLM). . . . . . Online tutorial: https://google.github.io/CFU-Playground/ For reference docs, see the link below.
tf2-bot-kicker - A python program that kicks those nasty name-stealing bots in TF2
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.
tfops-aug - TFOps-Aug: Implementation of policy-based image augmentation techniques based on TF2 Operations. All augmentations as efficient Tensorflow 2.11.0 operations. Easy integration into a tf.data API pipeline.