Author: Deep Learner

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Azure AI milestone: New foundation model Florence v1.0 advances state of the art, topping popular computer vision leaderboards

The Project Florence Team With the new computer vision foundation model Florence v1.0, the Project Florence team set the new state of the art on the popular leaderboards TextCaps Challenge 2021, nocaps, Kinetics-400/Kinetics-600 action classification, and OK-VQA Leaderboard.  Florence v1.0—along with recent milestones in Neural Text-to-Speech and question answering—is part of a larger Azure AI mission to provide relevant, meaningful AI solutions and services that work better for people because they better capture how people learn and

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Python

Host Your Django Project on Heroku

As a novice web developer, you’ve built your portfolio app and shared your code on GitHub. Perhaps, you’re hoping to attract technical recruiters to land your first programming job. Many coding bootcamp graduates are likely doing the same thing. To differentiate yourself from the crowd and boost your chances of getting noticed, you can start hosting your Django project online. For a hobby Django project, you’ll want a hosting service that’s free of charge, quick to set up, user-friendly, and […]

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Generator

Archive of the image generator stuff from my API

Archive of the image generator stuff from my API Q: Why?A: Because I am removing these components from the API Q: How do I run it?A: You use quart (Flask, but with async) and blueprints. I won’t copy-paste the entire API for people to instantly steal it, if that’s what you thought you could do. Q: Can I use it for my API?A: Yes, but give credits in some way GitHub View Github    

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Dynamic

Life Dynamics for python

run command must be like this: /usr/bin/python3 /home/nmakagonov/Daphny/daphny_counter/Daphny_counter.py -o /home/nmakagonov/Daphny/out.txt –path /media/nmakagonov/DiskD/NN_DATA/daphniacounter/DataForTraining/DataForTraining/MediumPopulation/medium_normal_RawImage/ -st 300 -sp 500where -o :path to the output text file where the counting result will be saved –path path to the directory with daphny-images -st number of the first frame for analysis -sp number of the last frame for analysis GitHub View Github    

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Segmentation

Deep Level Set for Box-supervised Instance Segmentation in Aerial Images

Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu* Any questions or discussions are welcomed! Installation Please refer to INSTALL.md for environment installation. This code is based on MMdetection and AerialDetection. Getting Started Please see GETTING_STARTED.md for the dataset preparation and basic usage. Visualization Instance segmentation results only under the supervision of box annotations on iSAID dataset. To Do COCO dataset Medical images Text images Citation

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Search

The Neurips 2021 paper Searching Parameterized AP Loss for Object Detection

By Chenxin Tao,Zizhang Li,Xizhou Zhu,Gao Huang,Yong Liu,Jifeng Dai This is the official implementation of the Neurips 2021 paper Searching Parameterized AP Loss for Object Detection. Introduction TL; DR. Parameterized AP Loss aims to better align the network training and evaluation in object detection. It builds a unified formula for classification and localization tasks via parameterized functions, where the optimal parameters are searched automatically. Introduction. In evaluation of object detectors, Average Precision (AP) captures the performance of localization and classification sub-tasks […]

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