text stringlengths 1 93.6k |
|---|
initial_img = normalize_image(np.float32(initial_img.cpu()[0].permute(1, 2, 0).data.numpy()))
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# from now :
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# - heatmap : numpy array with values between 0 and 1
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# - initial_img : numpy array with values between 0 and 1
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heatmap = cv2.resize(heatmap, (initial_img.shape[0], initial_img.shape[1])) # interpolation of the heatmap
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heatmap = np.uint8(255 * heatmap) # convert between 0 and 255
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heatmap = cv2.applyColorMap(heatmap, cv2.COLORMAP_JET) # infer the heatmap colorization
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heatmap = np.float32(heatmap) / 255. # convert between 0 and 1
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superimposed_img = heatmap + initial_img # merge heatmap & initial image
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superimposed_img = normalize_image(superimposed_img) # normalize the produced image
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superimposed_img = np.uint8(255 * superimposed_img) # convert between 0 and 255
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cv2.imwrite(produced_img_path, superimposed_img)
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print("Interpretable image registred at : {}".format(produced_img_path))
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def get_main_coeffs(term_1, term_2):
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"""
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Input:
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term_1, term_2: vectors
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Output:
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indices of the coefficients that contribute the most to the score
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resulting from the dot product of `term_1` and `term_2`.
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"""
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return (term_1 * term_2).detach().cpu()[0].sort()[1][-NUMBER_OF_MAIN_COEFF:] # [0] because we consider the first (and unique) element of the batch
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################################################################################
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#### MAIN
|
if __name__ == '__main__':
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args = verify_input_args(parser.parse_args())
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# Load model
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args, model, vocab = load_model(args)
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# Generate heatmaps
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main_generate_heatmaps(args, model, vocab)
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# <FILESEP>
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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# Python script to convert Forex files into different formats (e.g. FXT/HST/HCC).
|
from struct import pack, pack_into, calcsize
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import argparse
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import bstruct
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import csv
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import datetime
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import mmap
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import os
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import re
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import sys
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import time
|
class Spinner:
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"""Displays an ASCII spinner"""
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def __init__(self, step):
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self._n = self._x = 0
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self._chars = "\\|/-"
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self._step = step
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def spin(self):
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self._n += 1
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if self._n % self._step == 0:
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sys.stdout.write("\b" + self._chars[self._x % 4])
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sys.stdout.flush()
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self._x += 1
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if self._x >= 4:
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self._x = 0
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self._n = 0
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spinner = Spinner(100000)
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class Input:
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def __init__(self, path):
|
if args.verbose:
|
print("[INFO] Trying to read data from %s..." % path)
|
try:
|
self.path = open(path, "r")
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except OSError as e:
|
print(
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"[ERROR] '%s' raised when tried to read the file '%s'"
|
% (e.strerror, e.filename)
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)
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sys.exit(1)
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self.uniBars = []
|
def __del__(self):
|
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