jogam5’s gists

jogam5 / tenyks_cli.py

Created June 22, 2023 03:36

	import subprocess
	import time

	def automate_cli_input(cli_command, input_values):
	# Start the CLI subprocess
	cli_process = subprocess.Popen(cli_command.split(), stdin=subprocess.PIPE,
	stdout=subprocess.PIPE, universal_newlines=True)

	# Iterate over the expected input prompts
	for prompt, value in input_values.items():

jogam5 / roboflow_datasets.py

Created June 22, 2023 03:34

	import shutil
	import os
	import json
	from PIL import Image

	def copy_from_to(file_path_from, file_path_to):
	shutil.copy(file_path_from, file_path_to)

	def copy_subset_of_kitti(input_folder_path, output_folder_path, idx_begin='000000', idx_end='001000'):
	# Improvements:

jogam5 / datasets_util.py

Created June 22, 2023 03:26

	import roboflow_datasets as roboflow
	import os
	import shutil

	def make_dir(new_dir_path):
	if not os.path.exists(new_dir_path):
	os.makedirs(new_dir_path)
	print(f'{new_dir_path} created')

	def copy_from_to(file_path_from, file_path_to):

jogam5 / subprocess_tao_nvidia.py

Created December 19, 2022 05:39

subprocesses python library

	THIS WORKS!
	import subprocess
	cmd = ['tao', 'yolo_v4_tiny', 'export', '-m',
	'/workspace/tao-experiments/yolo_v4_tiny/experiment_dir_retrain/weights/yolov4_cspdarknet_tiny_epoch_005.tlt',
	'-k', 'YOUR_KEY',
	'-e', '/workspace/tao-experiments/yolo_v4_tiny/specs/yolo_v4_tiny_retrain_kitti.txt',
	'-o', '/workspace/tao-experiments/yolo_v4_tiny/export/yolov4_cspdarknet_tiny_epoch_005.etlt',
	'--data_type', 'fp32',
	'--gen_ds_config']

jogam5 / latent.txt

Last active April 20, 2022 22:43

	# For the best DCGAN generator
	# 1. covid small
	# 2. rsna_10
	# 3. rsna_50

	noise = np.random.normal(0, 1, (100, 128))
	gen_sample = generator.predict([noise, label]) # e.g. label is 0 or 1 in RSNA

	# gen_sample in keras outputs (100, 64, 64, 3)
	# e.g. for rsna_10 i need two vectors (100, 64, 64, 3), one for each lass

jogam5 / wwmse_v1.txt

Last active December 8, 2021 05:36

wwmse example

	# Note: 1 and 2 are simplifications to be more clear
	# 1. Generate distribution: simplification
	data_from_distribution = generate_rayleigh_CSI(parameter_1, parameter_2, parameter_3, ...)

	# 2 Loop over data to compute wwmse: simplification
	for sample in range(data_from_distribution):

	wwmse = WMMSE(number_of_transceivers, sample, max_power_budget, noise)
	# ==Parameters==:
	#

jogam5 / InvertedIndex.java

Created October 22, 2021 01:35

Inverted Index using MapReduce

	package my.index;

	import java.io.*;
	import java.util.*;
	import org.apache.hadoop.fs.Path;
	import org.apache.hadoop.io.*;
	import org.apache.hadoop.conf.Configuration;
	import org.apache.hadoop.mapreduce.Job;
	import org.apache.hadoop.mapreduce.Mapper;
	import org.apache.hadoop.mapreduce.Reducer;

jogam5 / Grep.java

Created October 22, 2021 01:29

Grep in MapReduce

	package my.midterm;

	/*
	'Overview' section provides a concise high level summary of Hadoop - MapReduce:
	https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html
	*/

	import java.io.*;
	import java.util.*;
	import org.apache.hadoop.fs.Path;

jogam5 / TwiLex

Last active July 28, 2020 14:12

	Autodials (Github examples)
	https://github.com/sloan58/twilio-autodialer
	https://github.com/cristeab/autodialer

	Build IVR with Lex
	https://cogint.ai/conversational-ivr-with-amazons-lex-and-connect/

	Amazon Lex Developer Resources
	https://aws.amazon.com/lex/resources/
	https://github.com/awslabs/aws-lex-browser-audio-capture

jogam5 / Docker_GO_Options.txt

Last active July 21, 2020 19:21

Create a Dockerfile for GO

J Gabriel jogam5