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probably weight training rn!

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probably weight training rn!
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aafaqin / gist:b82eb233f66da28d84749a4bdec37f7f
Last active March 23, 2026 16:50
Privacy Policy for DeepXP

Privacy Policy for DeepXP

Last updated: March 2026

DeepXP ("we", "our", or "us") respects your privacy. This Privacy Policy explains how we collect, use, store, and protect your information when you use the DeepXP mobile application (the "App").

1. Information Collection and Use

DeepXP is designed as an offline-first productivity tool. The core functionality of the App operates primarily on your device using local storage.

@aafaqin
aafaqin / readme.md
Created November 8, 2021 11:53
Jetson Xavier AGX Installation

Setting up Nvidia Jetson Xavier AGX

  • NVIDIA SDK Manager is used for NVIDIA’s Jetson. Ubuntu 18.04 LTS Highly recommended. Doesn't work otherwise.

  • Download SDK manager from this link https://developer.nvidia.com/nvidia-sdk-manager

  • Ubuntu: from a terminal window, install the Debian package with the command:

#starting from 11 to 33 the array contains the timestamps of the video and each sub part will be 4 seconds after that.
array=(00:07:43 00:07:52 00:08:07 00:08:25 00:08:38 00:09:19 00:09:27 00:09:40 00:10:06 00:10:23 00:10:32 00:10:53 00:11:03 00:11:17 00:11:41 00:12:01 00:12:15 00:13:01 00:13:15 00:13:32 00:13:50)
counter=0
for i in `seq -w 11 33`
do
ffmpeg -i VID_20210218_172619.mp4 -ss "${array[counter]}" -t 00:00:04 -c copy "cut""$i.mp4"
echo ${array[counter]} >> dump.txt
((counter++))
done
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aafaqin / ransac_polyfit.py
Created March 17, 2021 10:05 — forked from geohot/ransac_polyfit.py
RANSAC polyfit. Fit polynomials with RANSAC in Python
def ransac_polyfit(x, y, order=3, n=20, k=100, t=0.1, d=100, f=0.8):
# Thanks https://en.wikipedia.org/wiki/Random_sample_consensus
# n – minimum number of data points required to fit the model
# k – maximum number of iterations allowed in the algorithm
# t – threshold value to determine when a data point fits a model
# d – number of close data points required to assert that a model fits well to data
# f – fraction of close data points required
besterr = np.inf
# Default ignored files
/shelf/
/workspace.xml
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml
# Editor-based HTTP Client requests
/httpRequests/