athmanar

import openai
from openai import OpenAI
import os
import pandas as pd
import time
import os


def get_completion(prompt):
	client = OpenAI(api_key='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', )

athmanar

conda create --name genai python=3.8

athmanar

import csv
import numpy as np
import matplotlib.pyplot as plt
plt.ion()
def parse_csv_file(filename):
    data = []

    with open(filename, 'r') as csvfile:
        reader = csv.reader(csvfile)
        for row in reader:

athmanar

# cd /export/ssl-nfs1/shared/datasets/ILC_Gesture_Complex_ILC/processed_data/Hui_708_3/radar_top25_np
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
points=np.load('radar_Hui_right_hand_palm_down_50_dx_0_08_Jul_2022_15_02_08_fft_72.np')
RadarPC = points[:,[5,6,7,2,1]]
points=RadarPC
mask= (points[:,:3]>=0) * (points[:,:3]<=1.0)
mask2=mask[:,0]*mask[:,1]*mask[:,2]
p=points[mask2]

athmanar

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
def plot_histogram_with_kde(vector, bins=30):
    """
    Plot a histogram with a Kernel Density Estimate (KDE) on top.

    Args:
    - vector (list or ndarray): Data vector.
    - bins (int): Number of histogram bins.

athmanar

screen -L -Logfile test.txt -S test
screen -XS <session-id> quit

athmanar

import numpy as np
from scipy.io import loadmat
import os
import glob
fullist=glob.glob('/export/ssl-nfs1/shared/datasets/ILC_Gesture_Complex_ILC/processed_data_final/*/radar_top25_np/*.np')
np.random.shuffle(fullist)

# datlist=np.load('/export/ssl-nfs1/shared/datasets/VLP16TICAMCALIB_HUMAN_SMALL/train_val_aug_18_v1.npy',allow_pickle=True)
# fullist=datlist.item()['train']+datlist.item()['val']

athmanar

We couldn’t find that file to show.

athmanar

from argparse import Namespace
def nested_dict_to_namespace(dictionary):
    namespace = dictionary
    if isinstance(dictionary, dict):
        namespace = Namespace(**dictionary)
        for key, value in dictionary.items():
            setattr(namespace, key, nested_dict_to_namespace(value))
    return namespace

athmanar

import visdom
from visdom import Visdom
import numpy as np
import argparse
import numpy as np
import math
import os.path
import time
import tempfile
import urllib