| Name | Version | Summary | date |
| PytorchWildlife |
1.0.2.14 |
a PyTorch Collaborative Deep Learning Framework for Conservation. |
2024-05-08 22:03:42 |
| hume |
0.5.1 |
Hume AI Python SDK |
2024-05-02 17:04:04 |
| imghdr2 |
3.11 |
A lightweight Python library for determining the type of image files, as a separate module due to official deprecation. |
2024-04-29 04:21:58 |
| Robocon-24 |
0.3.3 |
This project is designed to detect balls and make decisions based on their positions in the context of a Robocon competition. |
2024-04-27 20:42:30 |
| bark-detection |
0.1.2 |
Package for bark detection in audio file |
2024-04-23 09:24:44 |
| tensorrt-yolo |
3.0.1 |
TensorRT-YOLO: Support YOLOv5, YOLOv8, YOLOv9, PP-YOLOE using TensorRT acceleration with EfficientNMS! |
2024-04-23 08:34:08 |
| faster-eTaPR |
0.1.2 |
None |
2024-04-08 18:17:07 |
| discminer |
0.2.32 |
Python package for parametric modelling of intensity channel maps from gas discs |
2024-04-08 03:55:56 |
| exordium |
1.2.5 |
Collection of utility tools and deep learning methods. |
2024-04-02 15:24:30 |
| docspotter |
0.3 |
DocSpotter is a Python library designed to extract specific information from document images by combining text detection and extraction technologies. |
2024-04-01 12:15:00 |
| fastanpr |
0.1.13 |
A fast automatic number-plate recognition (ANPR) library |
2024-03-30 13:47:14 |
| fingerprint-pro-server-api-sdk |
6.0.0 |
Fingerprint Pro Server API allows you to get information about visitors and about individual events in a server environment. It can be used for data exports, decision-making, and data analysis scenarios. Server API is intended for server-side usage, it's not intended to be used from the client side, whether it's a browser or a mobile device. |
2024-03-27 22:40:42 |
| thetis |
0.2.0 |
Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines) for uncertainty consistency (calibration), fairness, and other safety-relevant aspects. |
2024-03-22 08:37:22 |
| thetiscore |
0.2.0 |
Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines) for uncertainty consistency (calibration), fairness, and other safety-relevant aspects. |
2024-03-22 08:36:57 |
| seapipe |
0.1 |
A package pipeline for Sleep Events Analysis of EEG data. |
2024-03-21 01:30:47 |