NickShargan

import numpy as np


def get_coord_bazises(point_1, point_2):
    """"Function defines coordinate system basizes: Oz as vector parrallel to line point_1, point_2
    Ox as random orthogonal vector to Oz, and Oy as vector orthogonal to Oz and Ox.
    """
    vec_z = point_2 - point_1
    vec_z = vec_z / np.linalg.norm(vec_z)

NickShargan

Ubuntu 22.04 for Deep Learning

In the name of God

This gist contains steps to setup Ubuntu 22.04 for deep learning.

---

Install Ubuntu 22.04

NickShargan

Install OpenOCD

1. Install openocd following instructions:

git clone https://github.com/ntfreak/openocd
cd openocd

sudo apt-get install build-essential pkg-config autoconf automake libtool libusb-dev libusb-1.0-0-dev libhidapi-dev libftdi-dev

./bootstrap

NickShargan

sudo apt-get remove docker docker-engine docker.io containerd runc

sudo apt-get update

sudo apt-get install -y \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common

NickShargan

import os
import numpy as np

from keras.applications.mobilenet import MobileNet
from keras.models import Sequential, Model
from keras.layers import Input, Dense, Activation, GlobalAveragePooling2D, Reshape, Conv2D, Dropout
from keras.optimizers import adam
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ModelCheckpoint, TensorBoard, ReduceLROnPlateau, EarlyStopping
from keras.backend import backend

NickShargan

from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.layers import BatchNormalization, GlobalAveragePooling2D
from keras.optimizers import SGD
import numpy as np
import time

img_size = 128

NickShargan

(server)  jupyter notebook --no-browser --port=8080
(machine) ssh -N -L 8080:localhost:8080 <remote_user>@<remote_host> [-p <port_number>]
(machine) http://localhost:8080/ (+ type token)

NickShargan

package tfexample.myapp.com.myapplication

import android.os.Bundle
import android.support.v7.app.AppCompatActivity
import android.util.Log
import org.tensorflow.contrib.android.TensorFlowInferenceInterface
import kotlin.system.measureTimeMillis


val modelName = "file:///android_asset/mobile_unet_160_100_100.pb"

NickShargan

import numpy as np
import cv2

video_path = "./vid.mp4"

cap = cv2.VideoCapture(video_path)
target_shape = (640, 360)

fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()

NickShargan

import numpy as np
import cv2


video_path = "./vid.mp4"

cap = cv2.VideoCapture(video_path)

if not cap.isOpened():