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| import requests | |
| from lxml import html | |
| import pandas as pd | |
| def scrape_table_with_links(url): | |
| """ | |
| Scrapes a table from a webpage, extracting both text and URLs from cells. | |
| Specifically targets //form/table/tbody/tr[td] and extracts URLs from column 3. | |
| Args: |
MarcoForte
/ add_zoom_crop.py
Created
August 20, 2020 13:24
Overlay zoomed in crop on image. Used for creating images in FBA Matting paper.
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| def add_zoom_crop(img, crop_xs, crop_ys, r, inset_coord): | |
| x1,x2 = crop_xs | |
| y1,y2 = crop_ys | |
| img = (img*255).astype(np.uint8) | |
| inset_coord_end = ( int(inset_coord[0]+(x2-x1)*r), int(inset_coord[1] +(y2-y1)*r)) | |
| patch = img[y1:y2,x1:x2] | |
| patch_bigger = cv2.resize(patch, ( int(patch.shape[1]*r), int(patch.shape[0]*r))) | |
| img[inset_coord[1]:inset_coord[1]+patch_bigger.shape[0], inset_coord[0]:inset_coord[0]+patch_bigger.shape[1]] = np.atleast_3d(patch_bigger) | |
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| ######################## | |
| # https://gist.github.com/alper111/b9c6d80e2dba1ee0bfac15eb7dad09c8 | |
| def gauss_kernel(size=5, device=torch.device('cpu'), channels=3): | |
| kernel = torch.tensor([[1., 4., 6., 4., 1], | |
| [4., 16., 24., 16., 4.], | |
| [6., 24., 36., 24., 6.], | |
| [4., 16., 24., 16., 4.], |
MarcoForte
/ group_weight.py
Created
April 12, 2020 13:04
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| def group_weight(module, lr_encoder, lr_decoder, WD): | |
| group_decay = { 'encoder': [], 'decoder':[]} | |
| group_bias = { 'encoder': [], 'decoder':[]} | |
| group_GN = { 'encoder': [], 'decoder':[]} | |
| for name, m in module.named_modules(): | |
| # if hasattr(m, 'requires_grad'): | |
| # if m.requires_grad: | |
| # continue |
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| name: "color" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 4 | |
| input_dim: 256 | |
| input_dim: 256 | |
| layer { | |
| name: "data_l_ab_mask" | |
| type: "Input" | |
| top: "data_l_ab_mask" |
MarcoForte
/ REDNet_ch3.prototxt
Created
July 5, 2017 16:15
Just for quick visualisation with netscope
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| name: "RED-Net" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 256 | |
| input_dim: 256 | |
| # conv1 | |
| layer { | |
| name: "conv1" |
MarcoForte
/ FactorFactorial
Created
August 31, 2015 18:41
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# Primarily about computing factorials" | |
| ] | |
| }, | |
| { |
MarcoForte
/ Evolution of a Python programmer.py
Last active
August 29, 2015 14:05
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| #Newbie programmer | |
| def factorial(x): | |
| if x == 0: | |
| return 1 | |
| else: | |
| return x * factorial(x - 1) | |
| print factorial(6) | |
| #First year programmer, studied Pascal |
MarcoForte
/ fileDuration.py
Last active
August 29, 2015 14:05
Get audio or video file duration with Powershell through Python on Windows
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| """ This module shows how to retrieve the duration of an audio or video file on Windows by getting the file details | |
| with Powershell, tested on Powershell 4. """ | |
| import subprocess | |
| myFileLocation = r"'C:\Users\Marco\Untitled.wma'" # or myFileLocation = 'C:\\Users\\yourname\\test.mp4' | |
| def getFileDuration(fileLocation): | |
| # Calls the Powershell script that gets the file duration | |
| return subprocess.check_output([r'C:\WINDOWS\system32\WindowsPowerShell\v1.0\powershell.exe', | |
| '(((New-Object -COMObject Shell.Application).Namespace((Split-Path {0})))).GetDetailsOf((((New-Object -COMObject Shell.Application).Namespace((Split-Path {0}))).ParseName((Split-Path {0} -Leaf))), 183);'.format(myFileLocation)]).decode("utf-8").splitlines()[0] |