Model Assisted Object Labeling Toolkit
Project description
Model Assisted Labeling Toolkit
Malt allows users to quickly create labeled images from a video with the help of a predefined model. Creating good training data for object recognition is an iterative process, and malt is designed to speed up each iteration. The typical malt workflow will go as follows:
- Create a sparsely trained Tensorflow Lite Model
- Load and scan through a video to find object positions that are unfamiliar to the model and label those frames
- Adjust the auto-generated bounding boxes to perfectly fit the target object
- Save the labeled frames as images
- Train a new model
- Load the new model and a new video
- Repeat the process
Install & Launch Malt
pip3 install maltk malt or python3 -m malt
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file maltk-0.0.0.1.tar.gz.
File metadata
- Download URL: maltk-0.0.0.1.tar.gz
- Upload date:
- Size: 12.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
084e3b6037fc2513662181de7ef62af5ceebe4cbae025090ce887764b262279d
|
|
| MD5 |
19b66e6927a83839884b6fbb8b1649e8
|
|
| BLAKE2b-256 |
e6b0044ef001b8bd2bbf07c38e74b18c7dbf0d80c728b9bcc56cc4533ed864dc
|
File details
Details for the file maltk-0.0.0.1-py3-none-any.whl.
File metadata
- Download URL: maltk-0.0.0.1-py3-none-any.whl
- Upload date:
- Size: 14.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
af32fb30f9130b3015a74f46568374e304784af3ea1bc4541dd6f34d5aefe4cf
|
|
| MD5 |
aadee75a684a005a83fd99343ad6270c
|
|
| BLAKE2b-256 |
226d2290293c6e13b02fbb20d4bcd91f05475d5b4bdc45781d3e3003159bf8f8
|