import os
import numpy as np
from LOGS import LOGS
from PIL import Image
def create_gradient_image(
imageFile: str, width: int = 100, height: int = 100, scale: float = 1
):
"""Create a small gradient image.
Args:
width: Image width in pixels (default: 100)
height: Image height in pixels (default: 100)
Returns:
PIL Image object with gradient pixel values
"""
height = int(height * scale)
width = int(width * scale)
gradient_array = np.zeros((height, width, 3), dtype=np.uint8)
for i in range(height):
gradient_array[i, :] = [int(255 * i / height), int(255 * (1 - i / height)), 128]
image = Image.fromarray(gradient_array, mode="RGB")
image.save(imageFile)
return imageFile
# Connect to LOGS
logs = LOGS(configFile="/home/sina/src/logs-py/testing/logs_configs/release.json")
# Create a directory for a image gallery
os.mkdir("image_gallery")
file1 = create_gradient_image("image_gallery/random_image_1.png", scale=1)
file2 = create_gradient_image("image_gallery/random_image_2.png", scale=2)
file3 = create_gradient_image("image_gallery/random_image_3.png", scale=3)
# Create a image folder dataset with the three created image files
dataset = logs.newDataset(files=[file1, file2, file3], formatOrFormatId="image")
logs.create(dataset)
# Fetch the dataset file list
dataset.fetchFiles()
# create output directory for downloaded files
outputDir = "downloaded_files"
os.mkdir(outputDir)
# Select the first from the file list and download it
firstFile = dataset.files[0]
path = dataset.downloadFile(firstFile, directory=outputDir)
print(f"Image file '{path}' successfully downloaded from dataset {dataset}.")