Ricardo de Azambuja ricardodeazambuja

## MNIST Keras - Simple, but interactive.ipynb

      
              1 file
            
          
              1 fork
            
          
              0 comments
            
          
              0 stars
            
          
                ricardodeazambuja
                / MNIST Keras - Simple, but interactive.ipynb
            
            
              Last active
              February 19, 2024 14:38
            
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## setup.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
#
# To generate DEB package from Python Package:
# sudo pip3 install stdeb
# python3 setup.py --verbose --command-packages=stdeb.command bdist_deb
#
#
# To generate RPM package from Python Package:

## gcc compiler optimization for arm systems.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                ricardodeazambuja
                / gcc compiler optimization for arm systems.md
            
            
              Created
              March 9, 2023 21:32
                — forked from fm4dd/gcc compiler optimization for arm systems.md
            
              
                GCC compiler optimization for ARM-based systems
              
          
    GCC compiler optimization for ARM-based systems

2017-03-03 fm4dd
The gcc compiler can optimize code by taking advantage of CPU specific features. Especially for ARM CPU's, this can have impact on application performance. ARM CPU's, even under the same architecture, could be implemented with different versions of floating point units (FPU). Utilizing full FPU potential improves performance of heavier operating systems such as full Linux distributions.
-mcpu, -march: Defining the CPU type and architecture

These flags can both be used to set the CPU type. Setting one or the other is sufficient.

  
## add_repo_commit_to_hex.patch
# To apply this patch:
#  git apply add_repo_commit_to_hex.patch

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 04623c677..7a8005eea 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,5 +1,20 @@
 cmake_minimum_required(VERSION 3.13...3.18)


## install-adobe-reader-9-ubuntu-22.04.sh
# Cache sudo password
sudo -v

# Enable installation of 32-bit packages
sudo dpkg --add-architecture i386

# Install Adobe Reader
wget ftp://ftp.adobe.com/pub/adobe/reader/unix/9.x/9.5.5/enu/AdbeRdr9.5.5-1_i386linux_enu.deb
sudo dpkg -i AdbeRdr9.5.5-1_i386linux_enu.deb

## opencv_raw_capture_v4l2.py
# $ v4l2-ctl --list-formats-ext
# It shows my webcam supports MJPG and YUYV
# More details https://www.kernel.org/doc/html/v4.8/media/uapi/v4l/pixfmt-013.html

# And here we have some explanations about the flags available
# https://docs.opencv.org/4.x/d4/d15/group__videoio__flags__base.html

import cv2

cap = cv2.VideoCapture(0, cv2.CAP_V4L2) # I don't really need the CAP_V4L2 since it's the default

## Usage_Example_CrossEntropyLoss_and_BCELoss.py
# https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html
# https://pytorch.org/docs/stable/generated/torch.nn.BCELoss.html

import torch
from torch.nn import CrossEntropyLoss, BCELoss

# For this example:
# batch size = 1
# number of classes = 2
# size of tensors = 2x2

## using-google-takeout.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                ricardodeazambuja
                / using-google-takeout.md
            
            
              Created
              December 5, 2022 13:39
                — forked from chabala/using-google-takeout.md
            
              
                Merge and extract tgz files from Google Takeout
              
          
    Recently found some clowny gist was the top result for 'google takeout multiple tgz', where it was using two bash scripts to extract all the tgz files and then merge them together. Don't do that. Use brace expansion, cat the TGZs, and extract:
$ cat takeout-20201023T123551Z-{001..011}.tgz | tar xzivf -
You don't even need to use brace expansion. Globbing will order the files numerically:
$ cat takeout-20201023T123551Z-*.tgz | tar xzivf -

  
## semantic_segmentation.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                ricardodeazambuja
                / semantic_segmentation.ipynb
            
            
              Created
              October 7, 2022 19:04
                — forked from mortcanty/semantic_segmentation.ipynb
            
              
                Semantic_Segmentation.ipynb
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## gist:eb668cb015055f8c91eb9ed2f5f3ee43

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                ricardodeazambuja
                / gist:eb668cb015055f8c91eb9ed2f5f3ee43
            
            
              Created
              March 12, 2022 22:55
                — forked from rxaviers/gist:7360908
            
              
                Complete list of github markdown emoji markup
              
          
    People


 :bowtie:
😄 :smile:
😆 :laughing:


😊 :blush:
😃 :smiley:
☺️ :relaxed:


😏 :smirk:
😍 :heart_eyes:
😘 :kissing_heart:


😚 :kissing_closed_eyes:
😳 :flushed:
😌 :relieved:


😆 :satisfied:
😁 :grin:
😉 :wink:


😜 :stuck_out_tongue_winking_eye:
😝 :stuck_out_tongue_closed_eyes:
😀 :grinning:


😗 :kissing:
😙 :kissing_smiling_eyes:
😛 :stuck_out_tongue:
	#!/usr/bin/env python3
	# -- coding: utf-8 --
	#
	#
	# To generate DEB package from Python Package:
	# sudo pip3 install stdeb
	# python3 setup.py --verbose --command-packages=stdeb.command bdist_deb
	#
	#
	# To generate RPM package from Python Package:
	# To apply this patch:
	# git apply add_repo_commit_to_hex.patch

	diff --git a/CMakeLists.txt b/CMakeLists.txt
	index 04623c677..7a8005eea 100644
	--- a/CMakeLists.txt
	+++ b/CMakeLists.txt
	@@ -1,5 +1,20 @@
	cmake_minimum_required(VERSION 3.13...3.18)
	# Cache sudo password
	sudo -v

	# Enable installation of 32-bit packages
	sudo dpkg --add-architecture i386

	# Install Adobe Reader
	wget ftp://ftp.adobe.com/pub/adobe/reader/unix/9.x/9.5.5/enu/AdbeRdr9.5.5-1_i386linux_enu.deb
	sudo dpkg -i AdbeRdr9.5.5-1_i386linux_enu.deb
	# $ v4l2-ctl --list-formats-ext
	# It shows my webcam supports MJPG and YUYV
	# More details https://www.kernel.org/doc/html/v4.8/media/uapi/v4l/pixfmt-013.html

	# And here we have some explanations about the flags available
	# https://docs.opencv.org/4.x/d4/d15/group__videoio__flags__base.html

	import cv2

	cap = cv2.VideoCapture(0, cv2.CAP_V4L2) # I don't really need the CAP_V4L2 since it's the default
	# https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html
	# https://pytorch.org/docs/stable/generated/torch.nn.BCELoss.html

	import torch
	from torch.nn import CrossEntropyLoss, BCELoss

	# For this example:
	# batch size = 1
	# number of classes = 2
	# size of tensors = 2x2
`:bowtie:`	😄 `:smile:`	😆 `:laughing:`
😊 `:blush:`	😃 `:smiley:`	☺️ `:relaxed:`
😏 `:smirk:`	😍 `:heart_eyes:`	😘 `:kissing_heart:`
😚 `:kissing_closed_eyes:`	😳 `:flushed:`	😌 `:relieved:`
😆 `:satisfied:`	😁 `:grin:`	😉 `:wink:`
😜 `:stuck_out_tongue_winking_eye:`	😝 `:stuck_out_tongue_closed_eyes:`	😀 `:grinning:`
😗 `:kissing:`	😙 `:kissing_smiling_eyes:`	😛 `:stuck_out_tongue:`