Announcing PixLab Annotate - An Online Image Annotation Tool

The PixLab Computer Vision team is pleased to announce the immediate availability of PixLab Annotate. A web based image annotation, labeling & segmentation tool for Machine Learning model training tasks and beyond...

Annotate Features Set:

  • Rectangle, Polygon, Zoom & Drag labeling tool.
  • Consistent JSON output accepted by most Machine Learning frameworks.
  • Optimized for instance segmentation (Mask R-CNN, etc).
  • Client-side persistent storage - No data transfer involved.
  • Persistent & easy label management (Create, Modify & Delete).
  • Full screen display & Snapshot capture.

Straightforward image segmentation and labeling thanks to the Rectangle & Polygon built-in tool!

At PixLab, we really believe that annotate is a great fit for data scientists, developers or students looking for a straightforward, online image segmentation and labeling tool for their daily machine learning model training tasks and beyond...

Annotate Homepage

Feature & Support Requests

Tag Image Endpoint Enhancements

The PixLab team is pleased to announce major enhancement to the /tagimg endpoint.

The image labeling endpoint let you programmatically generates a description of an image in human readable language with complete sentences. The description is based on the visual content as reported by our state-of-the-art image labeling algorithm. More than one description can be generated for each image. Descriptions are ordered by their confidence score. All descriptions are in English.

the /tagimg endpoint documentation is available to consult here and below a working Python code sample:

import requests
import json

# Tag an image based on detected visual content which mean running a CNN on top of it.

# Target Image
img = '' 
# Your PixLab key
key = 'My_PixLab_Key'

req = requests.get('',params={'img':img,'key':key})
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
    total = len(reply['tags']) # Total tags
    print ("Total tags: "+str(total))
    for tag in reply['tags']:
        print("Tag: "+tag['name']+" - Confidence: "+str(tag['confidence']))

You can visit the PixLab Github repository for additional code samples in various programming languages.