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medical-diffusion-sam

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medical-diffusion-sam / data_loading.py

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Create data_loading.py

a70948b about 1 year ago

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	import os
	import csv
	import shutil
	import json
	from sam_api import segment_image_from_url
	import requests

	def process_data(data, output_csv, base_image_folder, segmented_image_folder):
	# Create the folders for base and segmented images if they don't exist
	os.makedirs(base_image_folder, exist_ok=True)
	os.makedirs(segmented_image_folder, exist_ok=True)

	# Open the CSV file and write the header
	with open(output_csv, 'w', newline='') as csvfile:
	fieldnames = ['base_image', 'segmented_image', 'description']
	writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
	writer.writeheader()

	# Iterate through the dataset
	for row in data['rows']:
	image_url = row['row']['image']['src']
	report = row['row']['report'].strip("b'")
	base_image_file = os.path.join(base_image_folder, f"base_image_{row['row_idx']}.jpg")
	segmented_image_file = os.path.join(segmented_image_folder, f"segmented_image_{row['row_idx']}.png")

	# Download and save the base image
	response = requests.get(image_url, stream=True)
	with open(base_image_file, 'wb') as out_file:
	shutil.copyfileobj(response.raw, out_file)
	del response

	# Segment the image and save it
	_ = segment_image_from_url(image_url)
	shutil.move('segmented_image.png', segmented_image_file)

	# Write the data to the CSV file
	writer.writerow({'base_image': base_image_file, 'segmented_image': segmented_image_file, 'description': report})

	# Example usage
	# Load the data from the JSON file
	with open('data.json', 'r') as json_file:
	data = json.load(json_file)


	output_csv = 'output.csv'
	base_image_folder = 'base_images'
	segmented_image_folder = 'segmented_images'

	process_data(data, output_csv, base_image_folder, segmented_image_folder)