anujonthemove
/ MNIST vanishing gradient.ipynb
Created
April 6, 2019 15:02
— forked from prhbrt/MNIST vanishing gradient.ipynb
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anujonthemove
/ sample_data_push_using_http_endpoints.py
Created
July 26, 2019 10:27
Sample data push to HTTP endpoints
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| import json | |
| import subprocess | |
| new_cdata='{"input": {"data": {"SensorMetaInfo": {"CameraDescription": "cisco_cam_type_1", "Ly": "20.98S", "Lx": "10.233N", "FeatureId": "9", "ServerId": "vijaywada_PC_01", "ProductCategoryId": "2", "CameraID": "akashwani_east", "LongDescription": "high range camera"}, "Data": {"CongressionThreshold": "20.0%", "ImageURL": "/home/anuj/git/work/end-to-end-api/hyderabad/deputy-01/vehicle-counter/output/2018-10-17/images/vehicle_counter_08:36:58.jpg", "Vehicles": {"AreaOccupied": "34.0%", "BikeCount": 2, "MiniBusCount": 0, "CarCount": 1, "ReportedTime": "2018-02-26t10:23:51", "HeavyVehicleCount": 0}, "VideoURL": "http://<ip-address>/video-analytics/hyderabad/akashwani_east/vehicle_counter/output/videos/2018_02_26_10_23_11_video.mp4", "CapturedTime": "2018-10-17 08:36:58.041400"}, "Event": {"EventID": 11, "EventDescription": "Threshold Congestion Exceeded"}}}, "configName": "Congestion", "groupName": "TrafficAnalytics", "tenantId": "vijayawada.com"}' | |
| subprocess.call(["curl", "-X", " |
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| # convert-mp4-to-webm-for-rtsp | |
| ffmpeg -i input-file.mp4 -c:v libvpx -crf 10 -b:v 1M -c:a libvorbis output-file.webm |
anujonthemove
/ backgroundAveraging.py
Created
May 24, 2020 13:03
— forked from TheSalarKhan/backgroundAveraging.py
Background Averaging (Background Subtraction) in Python+OpenCV
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| 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, |
anujonthemove
/ opencv-put-text-over-rectangle
Created
June 16, 2020 14:10
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| def text_over_rectangle(coords, text, image, color): | |
| x, y = coords | |
| # font | |
| fontFace = cv2.FONT_HERSHEY_SIMPLEX | |
| # org | |
| org = (20, 50) | |
| # fontScale | |
| fontScale = 2 |
anujonthemove
/ cv-util-cut-and-concatenate-videos.ipynb
Created
May 9, 2021 10:33
Cut and concatenate videos together using ffmpeg, python subprocess
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anujonthemove
/ cv-util-ffmpeg-convert-to-mp4-from-mkv-avi-asv-dav-mov.ipynb
Created
May 9, 2021 10:47
Convert to .mp4 from '.mkv', '.avi', '.asf', '.dav', '.mov' using ffmpeg, python subprocess
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anujonthemove
/ ds-util-exporting-pandas-df-to-pdf.ipynb
Created
May 9, 2021 10:53
Exporting stylized pandas dataframe to a pdf
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anujonthemove
/ mscoco_complete_label_map.csv
Last active
May 17, 2021 01:57
MS COCO complete 90 lables in csv along with their object ids for TensorFlow 1.15 Object Detection API models.
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| background | 0 | |
|---|---|---|
| person | 1 | |
| bicycle | 2 | |
| car | 3 | |
| motorcycle | 4 | |
| airplane | 5 | |
| bus | 6 | |
| train | 7 | |
| truck | 8 | |
| boat | 9 |