What does Yolov10 do?

Yolov10 focuses on detecting and labeling objects in images without needing to install software or code. It is catalogued under Computer vision, OCR & document AI on PulseGate.

Who should use Yolov10?

Yolov10 is a consumer product built for machine learning practitioners.

Does Yolov10 have a free plan?

Yes — Yolov10 is free to use.

What platforms does Yolov10 run on?

Yolov10 runs on the web. It can also be self-hosted.

Is Yolov10 still maintained?

Unverified. Yolov10 has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.

What are alternatives to Yolov10?

Similar projects tracked by PulseGate include YOLOv10 Web, Yolov6, and Yolo11.

Who develops Yolov10?

Yolov10 is developed by kadirnar.

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Yolov10

Name: Yolov10
Author: kadirnar

huggingface.coComputer vision, OCR & document AI

Yolov10 is a browser-based application that allows users to upload images and perform object detection using the YOLOv10 model. Users can select model size, adjust confidence and overlap thresholds, and receive annotated images with detected objects. It is designed for those needing quick, no-code object detection.

FreeWebSelf-hostedCloud-managed

Visit huggingface.co

1alternative

5features

2024since

Overview

5 features

Yolov10 is a Computer vision, OCR & document AI project. It focuses on detecting and labeling objects in images without needing to install software or code. Yolov10 is a consumer product aimed at machine learning practitioners. It is available for free. It runs on the web, and it can be self-hosted.

kadirnar builds and maintains Yolov10, and it first shipped in 2024. Key capabilities include object detection, image upload, and model selection.

Summary written by a language model from the project’s public pages.

Object detection
Image upload
Model selection
Threshold adjustment
Annotated output

Built with & integrations

Hosting

AWS

AI providers

local_oss

Runs on

BrowserSelf-hostedCloud-managed

Detected from

AWS: x-amz-cf-id header · x-amz-cf-pop header · via header
local_oss: huggingface in the HTML

Trust & compliance

Verified signals

HTTPSFree tier

Indexing history

What PulseGate has recorded for this listing

Indexed10 Jul · 21:51 UTC
kadirnar/Yolov10 verified via Hugging Face Enumerator
Source: Hugging Face Enumerator · Open

Frequently asked questions about Yolov10

What does Yolov10 do?: Yolov10 focuses on detecting and labeling objects in images without needing to install software or code. It is catalogued under Computer vision, OCR & document AI on PulseGate.
Who should use Yolov10?: Yolov10 is a consumer product built for machine learning practitioners.
Does Yolov10 have a free plan?: Yes — Yolov10 is free to use.
What platforms does Yolov10 run on?: Yolov10 runs on the web. It can also be self-hosted.
Is Yolov10 still maintained?: Unverified. Yolov10 has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
What are alternatives to Yolov10?: Similar projects tracked by PulseGate include YOLOv10 Web, Yolov6, and Yolo11.YOLOv10 Web Yolov6 Yolo11
Who develops Yolov10?: Yolov10 is developed by kadirnar.
When did Yolov10 launch?: Yolov10 first shipped in 2024.

At a glance

Platforms: Web
Languages: English
Built for: machine learning practitioners
Model: B2C
Solves: Detecting and labeling objects in images without needing to install software or code.

Registered as

Hugging Face Spaces: kadirnar/Yolov10

Developer

kadirnar

Index record

Indexed: 10 Jul 2026
Lifecycle: Alive
Last seen: 10 Jul 2026

Identity audit (12)

Slug: kadirnar-yolov10-huggingface-co
Lifecycle last checked: 8 Aug 2026
Verification state: Indexed for public listing
Listing state: Listed: yes
Index status: Included in index
Latest evidence snapshot: 10 Jul 2026
Timeline basis: Indexed-at chronology. This listing's first-seen date was written by the catalog backfill, not observed here, so it is not treated as a sighting.
Name from: Derived from the project's own page and URL.
Category from: Recorded source: taxonomy-pass-a.
Summary from: Written by a language model from public pages.
Languages from: Detected by a language model from page content.
Canonical URL: https://huggingface.co/spaces/kadirnar/Yolov10

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