Projects of Andfun Yangon

Overview

AndFunYangon

Projects of Andfun Yangon

First Commit

We can use gsearch.py to search for google image of any keyword and pass the file names into a csv file.

Second Commit

The face dection model has been implemented. You may need to download the face_cascade.xml and put it in the same directory with the python script for it to work.

Sample Run

Sample Run

csv

To Do

We need to implement some basic machine learning algorithm to extract the image with people or person in them We still need to download over 80 images, I am working on that and will be available very soon.

Reference

The image scraping script is referenced from Handhika Yanuar Pratama The face detection idea is refrenced from Mr. Khaing Htoo Ko.

Owner
Htin Aung Lu
Htin Aung Lu
D2LV: A Data-Driven and Local-Verification Approach for Image Copy Detection

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MTCNN face detection implementation for TensorFlow, as a PIP package.

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Code artifacts for the submission "Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems"

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Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.

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Disentangled Lifespan Face Synthesis

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UniFormer - official implementation of UniFormer

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General Multi-label Image Classification with Transformers

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This is the official repository of XVFI (eXtreme Video Frame Interpolation)

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Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

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Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization

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Vector.ai assignment

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PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs

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Implement face detection, and age and gender classification, and emotion classification.

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Fashion Recommender System With Python

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Contrastive Language-Image Pretraining

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PyTorch implementation of Histogram Layers from DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation

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Learning Energy-Based Models by Diffusion Recovery Likelihood

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