# zzh8829/yolov3-tf2

YoloV3 Implemented in Tensorflow 2.0

Repository: https://github.com/zzh8829/yolov3-tf2
Canonical: https://ross.abutalabs.com/products/yolov3-tf2
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: tensorflow, tf2, yolo, yolov3, object-detection, deep-learning, machine-learning, neural-network, tensorflow-tutorials, tensorflow-examples
Last push: 2024-08-30T23:51:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2709, "days_push": 733, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2513, forks 890 (observed 2026-08-28T04:06:57.530661+00:00)

## What it is
A clean implementation of YOLOv3 and YOLOv3-tiny object detection in TensorFlow 2.0, with pre-trained Darknet weight conversion, inference, and training examples. It supports eager and graph mode training, tf.data pipelines, GPU acceleration, and TensorFlow Serving deployment.

## Use cases
- run yolo object detection on images in tensorflow 2
- convert darknet yolov3 weights to tensorflow
- detect objects in video or webcam feed
- train yolov3 on a custom dataset
- transfer learning for object detection with keras
- deploy yolo model with tensorflow serving

## When to choose
- you want a readable, best-practices YOLOv3 implementation in TF2/Keras
- you need pre-trained weights plus a training tutorial for custom datasets
- you want GPU-accelerated detection with video and webcam support

## When to avoid
- you need the latest YOLO versions (v5/v8) or state-of-the-art accuracy
- you want a maintained production package rather than an educational codebase
- you don't use TensorFlow

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, computer-vision, image-processing, video-processing
- domain: deep-learning, computer-vision, machine-learning, image-processing
- platform: python, windows
- tags: yolov3, object-detection, tensorflow2, keras, transfer-learning, pretrained-weights, jupyter-notebook, gpu, linux, macos

## Member repositories
- zzh8829/yolov3-tf2 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:57.530661+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:26:19.146577+00:00, confidence not recorded.
  - readme: https://github.com/zzh8829/yolov3-tf2 (fetched 2026-08-28T04:06:57.530661+00:00, sha f01a42693e44)
- Data as of 2026-08-30T08:39:29.467469+00:00.