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import os
from PIL import Image
from collections import Counter
def analyze_images(directory):
analysis_results = {}
for root, dirs, files in os.walk(directory):
if files:
model_folder_name = os.path.basename(root)
if model_folder_name not in analysis_results:
analysis_results[model_folder_name] = {
'image_count': 0,
'total_size': 0,
'resolutions': Counter()
}
for file in files:
file_path = os.path.join(root, file)
# Count the image
analysis_results[model_folder_name]['image_count'] += 1
# Calculate the size of the image
try:
with Image.open(file_path) as img:
# Get the size of the image in bytes
file_size = os.path.getsize(file_path)
analysis_results[model_folder_name]['total_size'] += file_size
# Get image dimensions
width, height = img.size
analysis_results[model_folder_name]['resolutions'][(width, height)] += 1
except Exception as e:
print(f"Error reading file {file_path}: {e}")
return analysis_results
def print_and_log_analysis_results(analysis_results, dataset_name, log_file):
# Determine the maximum length of model names
max_model_length = max(len(model) for model in analysis_results.keys())
model_column_width = max(max_model_length, 20) # Ensure at least 20 characters
# Define column widths
image_count_width = 12
total_size_width = 14
resolution_width = 25
# Create header
header = f"{'Model':<{model_column_width}} | {'Image Count':>{image_count_width}} | {'Total Size (MB)':>{total_size_width}} | {'Most Common Resolution':<{resolution_width}}"
separator = "-" * (model_column_width + image_count_width + total_size_width + resolution_width + 7) # 7 for separators
result_lines = []
result_lines.append(f"Analysis for {dataset_name}:\n")
result_lines.append(header + "\n")
result_lines.append(separator + "\n")
for model, data in analysis_results.items():
total_size_mb = data['total_size'] / (1024 * 1024)
most_common_resolution = data['resolutions'].most_common(1)
if most_common_resolution:
common_res = f"{most_common_resolution[0][0][0]}x{most_common_resolution[0][0][1]} ({most_common_resolution[0][1]} images)"
else:
common_res = "None"
result_lines.append(f"{model:<{model_column_width}} | {data['image_count']:>{image_count_width}} | {total_size_mb:>{total_size_width}.2f} | {common_res:<{resolution_width}}\n")
result_lines.append("\n")
# Print to console
for line in result_lines:
print(line, end='')
# Write to log file
with open(log_file, 'a') as f:
f.writelines(result_lines)
def main():
# Define directories
generated_dir = 'resampledEvalSet'
real_dir = 'real'
log_file = 'analysis_results.txt'
# Clear the log file (optional, comment out if you want to append)
with open(log_file, 'w') as f:
pass
# Analyze generated images
generated_analysis_results = analyze_images(generated_dir)
print_and_log_analysis_results(generated_analysis_results, "Generated Images", log_file)
# Analyze real images
real_analysis_results = analyze_images(real_dir)
print_and_log_analysis_results(real_analysis_results, "Real Images", log_file)
if __name__ == "__main__":
main()
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