Search

Program that makes the daily searches for PC and Mobile for now

Program that makes the daily searches for PC and Mobile using Python and Selenium. The points you can win depends on the level of the account. First of all, you need to login to your account on Edge. The program uses the browser data to prevent the saving of credentials and avoid logging every time the program executes. Second, install the required dependencies: pip install -r requirements.txt & pip install -r requirements.txt Run the program and it automatically starts Edge […]

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PyTorch

Pytorch lightning tutorial using MNIST

Pytorch lightning tutorial using MNIST Youtube stream (Maybe there will be another… still planning!) Pytorch lightning introduction scheduler introduction (Japanese) Python>=3.7, creation using anaconda is recommended. Install libraries by pip install -r requirements.txt. Run (example) python train.py –root_dir “./” It will download the dataset to root_dir and start training. You can monitor the training process by launching tensorboard in another terminal: tensorboard –logdir logs And go to localhost:6006 in your browser. GitHub View Github    

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Django

Few hacks to speed up defining apis based on django rest framwork, inspired from fastapi

Few hacks to speed up defining APIs based on django rest framwork, inspired from fastapi First version tested on: python 3.9 and django 4.0 Features: Function based view Easy to use decorator Accepts validation of input and output using DRF serializers Accept CamelCased input and group all rest input methods in same dict :req Jsonify and camelcase any type of output: str, dict, QuerySet, Model AutoSchema docs using drf-spectacular Error handler that works with DRF Better way to pass the […]

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Transformer

Official Pytorch code for OW-DETR: Open-world Detection Transformer

[Paper] Akshita Gupta*, Sanath Narayan*, K J Joseph, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (🌟 denotes equal contribution) Introduction Open-world object detection (OWOD) is a challenging computer vision problem, where the task is to detect a known set of object categories while simultaneously identifying unknown objects. Additionally, the model must incrementally learn new classes that become known in the next training episodes. Distinct from standard object detection, the OWOD setting poses significant challenges for generating quality candidate proposals on […]

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Tool

A very simple tool that compresses the overall size of the ONNX model by aggregating duplicate constant values as much as possible

A very simple tool that compresses the overall size of the ONNX model by aggregating duplicate constant values as much as possible. Simple Constant value Shrink for ONNX. If the same constant tensor is found by scanning the entire graph for Constant values, it is aggregated into a single constant tensor. Ignore scalar values. Ignore variables. 1. Setup

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Steam

A plugin loader for the Steam Deck

Installation Go into the Steam Deck Settings Under System -> System Settings toggle Enable Developer Mode Scroll the sidebar all the way down and click on Developer Under Miscellaneous, enable CEF Remote Debugging Place the executable under ~/homebrew/services/plugin_loader. Do not change the name of the file. Place the plugin_manager.service file under /etc/systemd/system Open a Terminal and type systemctl –now –user enable plugin_manager Install Plugins Simply copy the plugin’s .py file into ~/homebrew/plugins Features Clean injecting and loading of one or […]

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Reddit

Reddit Drawing Bot Running Instructions

Setting up the requirements Download the Python installer from here Make sure “Add Python 3.9 to PATH is ticked Click on Customize installation, and make sure everything is ticked Click on “Next” Make sure “Add Python to environment variables” is ticked” Click install. and let it go Python Package Requirements To run the bot for the first time, install the requirements. Windows pip install -r requirements.txt simply open the directory you’ve extracted the bot to, and type cmd in the […]

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Humans

PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)

Kehong Gong*, Bingbing Li*, Jianfeng Zhang*, Tao Wang*, Jing Huang, Bi Mi, Jiashi Feng, Xinchao Wang CVPR 2022 (Oral Presentation, arxiv) Framework Pose-triplet contains three components: estimator, imitator and hallucinator The three components form dual-loop during the training process, complementing and strengthening one another. Improvement through co-evolving Here is imitated motion of different rounds, the estimator and imitator get improved over the rounds of training, and thus the imitated motion becomes more accurate and realistic from round 1 to 3. […]

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Deep Learning

DeepDPM: Deep Clustering With An Unknown Number of Clusters

This repo contains the implementation of our paper: DeepDPM: Deep Clustering With An Unknown Number of Clusters Meitar Ronen, Shahaf Finder and Oren Freifeld. DeepDPM clustering example on 2D data. On the left: DeepDPM’s predicted clusters’ assignments, centers and covariances. On the right: Clusters colored by the GT labels, and the net’s decision boundary. Examples of the clusters found by DeepDPM on the ImageNet Dataset: Table of Contents Introduction Installation Training Citation    

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Dashboard

Create Vega/Vega-Lite dashboards for Datasette

Build custom Vega/Vega-Lite dashboards in Datasette, for presentation-ready plots and visualizations. Installation Install this plugin in the same environment as Datasette. $ datasette install datasette-vega-dashboards Tutorial See the example fixture in example_fixture for a minimal example. You can run the fixture via: datasette -m metadata.json –template-dir templates/ sleep_log.db and then open http://127.0.0.1:8001/sleep_log/read_sleep to see the dashboard. In the minimal example, we create a canned query in metadata.json:

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