BMW-YOLOv4-Inference-API-GPU
nocode object detection inference API using Yolov3 and Yolov4 Darknet framework
GraphCanon updated Aug 14, 2026 · GitHub synced Aug 14, 2026
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Decision brief
BMW-YOLOv4-Inference-API-GPU offers no-code object detection services with support for YOLOv3 and YOLOv4 on the Darknet framework, optimized for deployment via Docker containers and GPU execution.
Good fit when
- When you need to deploy a no-code object detection API leveraging both YOLOv3 and YOLOv4 frameworks, and require high-performance inference with GPU support through Docker containerization.
- If your project requires the flexibility of deploying on either Docker or Docker Swarm, this tool is optimized for such scenarios.
Avoid when
- Avoid using BMW-YOLOv4-Inference-API-GPU if you need to perform inference without a GPU setup since it specifically leverages NVIDIA GPU drivers and does not provide native support for other hardware.
- Do not use this tool when needing multi-platform deployment out of the box, as the no-code interface and documentation focus primarily on Linux systems with Docker.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (1507d since push)
- As of Aug 14, 2026
- Provenance
- Not a fork · Organization account
- As of Aug 14, 2026
- Security (OSV)
- No lockfile
- As of Jul 15, 2026
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Install
pip install BMW-YOLOv4-Inference-API-GPUHow it fits your stack(1)
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Overview
Supplies an nocode object detection service with support for both YOLOv3 and YOLOv4, built on the Darknet framework. Optimized for deployment via Docker containers, allowing inference execution on GPU.
Capability facts
- Languages
- python
Source: github.language · Aug 14, 2026
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README
Install prerequisites Use the following command to install docker on Ubuntu: Install NVIDIA Drivers (410.x or higher) and NVIDIA Docker for GPU by following the official docs) Build The Docker Image In order to build the project run the following command from the project's root d...
For agents
This page has a .md twin and JSON over the API.