PatharaNor patharanordev

Solved ImportError: libGL.so.1: cannot open shared object file: No such file or directory

When using cv2 in Dockerfile.

Adding library below to your Dockerfile to solve the issue :

RUN apt-get update
RUN apt-get install ffmpeg libsm6 libxext6  -y

Plot image grid M x N via `matplotlib`

The example below, try to show predicted result image & label on VGG19 model, I have set grid size to N x 5 :

multi-rows
5-columns

I have directory structure like this

content

Long run CoLab

In CoLab, press (CTRL + SHIFT + i) to open inspect window. Go to console tab then press source code below and press enter :

function ClickConnect(){
console.log("Working"); 
document
 .querySelector('#top-toolbar &gt; colab-connect-button')

Encode image in nparray to base64

Encode base64 function:

import cv2
import base64

def encode_img(img, im_type):
 """Encodes an image as a png and encodes to base 64 for display."""

Fixed gem install cocoapods

If you found error message like this :

Error installing cocoapods: ERROR: Failed to build gem native extension

You should re-install ruby first before install cocoapods.

$ brew reinstall ruby

Convert `.pt` to `.onnx`

The function using in Scaled-YOLOv4, please refer to Scaled-YOLOv4 repository.

Before start, the export script requires onnxsim, you need to install it first :

$ pip install -q onnx-simplifier

If You are Using MAC, I Actually Solved this Issue By Granting Permission for Terminal To Access Camera in Security and Privacy Section in System Preferences. Hope This Solves Issue In Your Mac Click Here To View Steps

	mkdir coco
	cd coco
	mkdir images
	cd images

	wget http://images.cocodataset.org/zips/train2017.zip
	wget http://images.cocodataset.org/zips/val2017.zip
	wget http://images.cocodataset.org/zips/test2017.zip
	wget http://images.cocodataset.org/zips/unlabeled2017.zip

	echo "Press 'q' to continue"
	count=0
	while : ; do
	read -n 1 k <&1
	if [[ $k = q ]] ; then
	break
	fi
	done

	#!/usr/bin/env python

	import numpy as np
	import os
	import time

	os.environ['KERAS_BACKEND'] = 'plaidml.keras.backend'

	import keras
	import keras.applications as kapp