DeepDetect vs InsightFace
DeepDetect
deepdetect.comInsightFace
github.comSide by side
| Figure | DeepDetect | InsightFace |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 3 |
| Spec score · AI Image Recognition Software | 8.0 (#15) | 8.7 (#7) |
| Support | The plans page lists email support for Amazon AWS and email and phone support for Enterprise. | The open-source offering lists community support through GitHub Issues; commercial model licensing lists email support. |
Plans
DeepDetect
- Open SourceFree
- Amazon AWSPriced on request
- EnterprisePriced on request
InsightFace
- Open SourceFree
- Enterprise & APIPriced on request
- Model LicensingPriced on request
In their own words
DeepDetect
DeepDetect is an open-source deep-learning REST API server and web platform for training and managing models. Its listed application areas range from image tagging, object detection, segmentation, and OCR to audio, video, text classification, CSV data, and time-series. Training resources include Jupyter notebooks, dataset validation, hyperparameter presets, and distributed training across one or more GPUs. The platform advertises more than 50 pretrained models for transfer training, and models can be exported for cloud, desktop, or embedded devices. The server runs on CPU or GPU, accepts and returns JSON, and supports Mustache output templates; Elasticsearch is given as an example destination application. PyTorch and TensorRT are listed as backends, with TensorRT able to optimize NVIDIA GPU inference. Ready-to-use API examples are available for Shell, Python, and JavaScript. The free Open Source plan is free. Amazon AWS is priced on request, while the Enterprise plan has no listed price. Installation guidance covers Docker and a source build for Ubuntu 24.04 LTS.
InsightFace
InsightFace provides software for face detection, recognition, alignment, and attribute analysis, with optional liveness, person analysis, video face redaction, and face swapping. PersonAnalysis detects people and faces, then matches them to registered identities using face and body references. PrivateFrame supports local video face tracking and blur or mosaic redaction through desktop, command-line, and Python workflows. Integration options include Python, a C/C++ SDK, and a self-hosted REST API. InsightFace Server runs in a Linux container and offers a web interface, REST API, and Python SDK for detection, comparison, enrollment, search, and RTSP monitoring. The Python package uses ONNX Runtime and requires Python 3.10 or newer. The code is MIT licensed, but pretrained models are limited to non-commercial research unless separately licensed for commercial use. The maker presents enterprise applications such as identity verification, access control, mobile and edge authentication, and large-scale face search. Commercial model use requires a separate license.