# gliese581gg/YOLO_tensorflow

tensorflow implementation of 'YOLO : Real-Time Object Detection'

Repository: https://github.com/gliese581gg/YOLO_tensorflow
Canonical: https://ross.abutalabs.com/products/yolo_tensorflow
Language: Python
License: NOASSERTION
License Family: other
Last push: 2019-01-05T07:57:00+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3852, "days_push": 2797, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1708, forks 637 (observed 2026-08-28T04:05:25.470889+00:00)

## What it is
A TensorFlow implementation of YOLO (Real-Time Object Detection) that runs inference with pretrained YOLO_small, YOLO_tiny, and YOLO_face networks converted from darknet weights. It supports prediction only—training must be done with darknet—and can be used from the command line or imported into other Python scripts.

## Use cases
- detect objects in images with pretrained YOLO
- run YOLO inference in tensorflow
- convert darknet weights to tensorflow checkpoints
- detect faces in images with YOLO_face
- import YOLO detector into my python script
- output bounding boxes and class probabilities to a text file

## When to choose
- you need a simple, scriptable YOLO inference implementation in TensorFlow 1.x
- you want to reuse existing darknet YOLO weights without retraining
- you need a lightweight object detector importable into Python pipelines

## When to avoid
- you need to train or fine-tune YOLO models
- you need modern TensorFlow 2.x or current YOLO versions (v3+)
- you need commercial use—the license forbids it
- you need actively maintained code with recent updates

## Facets
- artifact type: library
- maturity: abandoned
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, image-processing, machine-learning, deep-learning
- platform: python, cross-platform
- tags: yolo, object-detection, tensorflow, pretrained-models, inference-only, darknet-weights

## Member repositories
- gliese581gg/YOLO_tensorflow (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:25.470889+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 2026-08-30T03:37:00.980445+00:00, confidence not recorded.
  - readme: https://github.com/gliese581gg/YOLO_tensorflow (fetched 2026-08-28T04:05:25.470889+00:00, sha 627fca46b7da)
- Data as of 2026-08-30T08:39:29.467469+00:00.