Simplify Model Building with Hosted Training​

175,000+ models trained with Roboflow
Train with Roboflow
0%
mAP
0%
Precision
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Recall

Training Infrastructure for Every Task and Environment

Hosted training for state of the art models, customized for your dataset, in no time.
Nano
2H 5M
Small
2H 5MI
Medium
2H 5M
Large
2H 5M
Extra Large
2H 5M
Accuracy

Select From 5 Model Sizes

Train nano models for fast iteration and low compute deployments or XL models for the highest level of accuracy
vials on a conveyor belt with bounding boxes around them
Object Detection
Classification
Keypoint Detection
Instance Segmentation
bottles in a factory with caps and body segmented
Semantic Segmentation
worker getting into a forklift - text over it says worker is wearing a helmet
Vision Language

Train Across 6 Task Types

Vision-language, object detection, classification, keypoint detection, instance segmentation, and semantic segmentation

Tools to Improve Your Models

Prototype, experiment, test, integrate, and deploy models to production.
Upload Image or Video File Drop file here or Select File
Try with a webcam
Test your model in the browser before deploying to production.
Original Raw Images 2 days ago v7 2485 COCOs-seg Accurate Modified Raw Images 1 day ago v8 2485 COCOs-seg Accurate Merged All Classes 8 hours ago v9 2485 COCOs-seg Accurate Augmented by 3x 1 hour ago v10 2485 COCOs-seg Accurate
Manage model versions to compare performance across multiple iterations.
microsoft-coco/10 93.4% mAP 95.7% precision 89.4% recall
Monitor metrics on mean average precision, recall, and more.

Model Understanding and Evaluation

Insights into how your vision models are performing to locate edge cases, anomalies, and areas of low performance.
Vector Analysis
Close-up of broken ball bearing
f1: 0.54
Bad
Good

Vector Analysis

Use semantic embeddings to find patterns in model failures and what type of data your models needs to better handle edge cases
Confusion Matrix
Defect
Correctly Predicted
False Positive Vehicle Defect 2934 835 28 1358 2834 17 80 34 0 Defect Vehicle False Negative

Confusion Matrix

Gain visibility into exactly where your model failed and use that data to improve the next version of your model

Immediate ROI From Your Custom Model

Deploy to production, use for model assisted labeling, or as a training checkpoint.
ARM CPU
x86 CPU
Luxonis OAK
NVIDIA GPU
NVIDIA TRT
NVIDIA Jetson
Raspberry Pi
ARM CPU
x86 CPU
Luxonis OAK
NVIDIA GPU
NVIDIA TRT
NVIDIA Jetson
Raspberry Pi
Python

CLIENT = InferenceHTTPClient(
    api_url="https://detect.roboflow.com",
    api_key="****"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="safety-vest-segmentation/4")

Deploy using out-of-the-box options with pre-built code snippets
cans on a conveyor beltcans on a conveyor belt with bounding boxes
22 Annotations added
Your model enables assisted labeling to speed up annotation work
Target Model Dataset Bottles - Overhead View Model v3 - Roboflow Fast Model (Bottles
Base Model Dataset Bottles - Overhead View Model v3 - Roboflow Fast Model (Bottles
Transfer learning from your model helps increase performance and get to production with less data