File size: 1,946 Bytes
a377382 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
import os
import json
# Define the directory where your dataset images are located
#dataset_directory = "cityscape_dataset"
# Define the directories for images and conditioning images
#image_dir = os.path.join(dataset_directory, "leftImg8bit/train")
#conditioning_dir = os.path.join(dataset_directory, "gtCoarse/train")
image_dir = "leftImg8bit/train"
conditioning_dir = "gtCoarse/train"
# Define the output JSONL filename
jsonl_filename = "train.jsonl"
# Initialize an empty list to store the dataset entries
dataset_entries = []
# Iterate through the city folders in the image directory
for city_folder in os.listdir(image_dir):
city_dir = os.path.join(image_dir, city_folder)
# Iterate through image files in the city directory
for image_filename in os.listdir(city_dir):
# Extract relevant information from the image filename
parts = image_filename.split("_")
city = parts[0]
seq = parts[1]
frame = parts[2]
# Construct the paths to the image and conditioning image
image_path = os.path.join(city_dir, image_filename)
conditioning_image_filename = f"{city}_{seq}_{frame}_gtCoarse_color.png"
conditioning_image_path = os.path.join(conditioning_dir, city_folder+"/"+conditioning_image_filename)
# Create a dataset entry as a dictionary
entry = {
"text": "A view to a street from a car's front window",
"image": image_path,
"conditioning_image": conditioning_image_path,
}
# Append the entry dictionary to the list
dataset_entries.append(entry)
# Open the JSONL file for writing
with open(jsonl_filename, "w") as jsonl_file:
# Write each entry as a JSON string followed by a newline character
for entry in dataset_entries:
jsonl_file.write(json.dumps(entry) + "\n")
print(f"JSON Lines file '{jsonl_filename}' has been created.")
|