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@georgekrax
georgekrax / commit-emojis.md
Last active March 21, 2024 14:51
List of emojis for GitHub commit messages
Emoji Purpose MD Markup Prefix
📄 Generic message :page_facing_up:
📐 Improve the format / structure of the code / files :triangular_ruler: [IMPROVE]:
Improve performance :zap: [IMPROVE]:
🚀 Improve something (anything) :rocket: [IMPROVE]:
📝 Write docs :memo: [PROD]:
💡 New idea
@fclesio
fclesio / get_classification_report.py
Created March 4, 2020 12:21
Scikit Learn Classification Report in Dataframe
def get_classification_report(y_test, y_pred):
'''Source: https://stackoverflow.com/questions/39662398/scikit-learn-output-metrics-classification-report-into-csv-tab-delimited-format'''
from sklearn import metrics
report = metrics.classification_report(y_test, y_pred, output_dict=True)
df_classification_report = pd.DataFrame(report).transpose()
df_classification_report = df_classification_report.sort_values(by=['f1-score'], ascending=False)
return df_classification_report
@anujonthemove
anujonthemove / opencv-videocapture-useful-properties.txt
Last active June 25, 2024 17:36
A handy list of VideoCapture object parameters taken from official OpenCV docs.
CAP_PROP_POS_MSEC =0, //!< Current position of the video file in milliseconds.
CAP_PROP_POS_FRAMES =1, //!< 0-based index of the frame to be decoded/captured next.
CAP_PROP_POS_AVI_RATIO =2, //!< Relative position of the video file: 0=start of the film, 1=end of the film.
CAP_PROP_FRAME_WIDTH =3, //!< Width of the frames in the video stream.
CAP_PROP_FRAME_HEIGHT =4, //!< Height of the frames in the video stream.
CAP_PROP_FPS =5, //!< Frame rate.
CAP_PROP_FOURCC =6, //!< 4-character code of codec. see VideoWriter::fourcc .
CAP_PROP_FRAME_COUNT =7, //!< Number of frames in the video file.
CAP_PROP_FORMAT =8, //!< Format of the %Mat objects returned by VideoCapture::retrieve().
CAP_PROP_MODE =9, //!< Backend-specific value indicating the current capture mode.
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@DominicBreuker
DominicBreuker / gd_simple.py
Created June 16, 2016 16:30
Simple example of gradient descent in tensorflow
import tensorflow as tf
x = tf.Variable(2, name='x', dtype=tf.float32)
log_x = tf.log(x)
log_x_squared = tf.square(log_x)
optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(log_x_squared)
init = tf.initialize_all_variables()
@TheSalarKhan
TheSalarKhan / backgroundAveraging.py
Last active February 12, 2023 03:47
Background Averaging (Background Subtraction) in Python+OpenCV
import numpy as np
import cv2
class BackGroundSubtractor:
# When constructing background subtractor, we
# take in two arguments:
# 1) alpha: The background learning factor, its value should
# be between 0 and 1. The higher the value, the more quickly
# your program learns the changes in the background. Therefore,