qualcomm/MediaPipe-Face-Detection

object-detection model by qualcomm

Open original source ↗

From the publisher

Model card & documentation

Source preview

Read the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.

Designed for sub-millisecond processing, this model predicts bounding boxes and pose skeletons (left eye, right eye, nose tip, mouth, left eye tragion, and right eye tragion) of faces in an image. This is based on the implementation of MediaPipe-Face-Detection found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here. Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device. There are two ways to deploy this…

qualcomm/MediaPipe-Face-Detection on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-09-20T06:40:43.160Z

Inside the original model card — Document outline
  1. MediaPipe-Face-Detection: Optimized for Qualcomm Devices
  2. Getting Started
  3. Option 1: Download Pre-Exported Models
  4. Option 2: Export with Custom Configurations
  5. Model Details
  6. Performance Summary
  7. License
  8. References
  9. Community

Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.

Links from the model card

References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.

Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

qualcomm/MediaPipe-Face-Detection is a object-detection model repository published by qualcomm on Hugging Face. The source reports the pytorch library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
object-detection
Library
pytorch
Recent downloads (30 days)
1,398
Cumulative likes
40
Hugging Face trending score
0
Reported safetensors parameters
Not reported
Architecture
Not reported
License
apache-2.0
Access
Not gated by Hugging Face
Created
2024-02-25T23:05:00.000Z
Last modified
2026-09-11T20:40:38.000Z

Compatibility and lineage

Language coverage was not reported.

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

Use and evaluate

Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.

No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.

Model card and usage instructions

Model files and configuration

Community discussion

Source and freshness

Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:53.017Z. Daily imports are snapshots, not real-time monitoring.

Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.

Open original source

Related models

mudler/locate-anything.cpp-gguf

PaddlePaddle/PP-DocLayoutV3_safetensors

microsoft/table-transformer-structure-recognition

PekingU/rtdetr_r101vd_coco_o365

hustvl/yolos-small

facebook/detr-resnet-50