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---
license: cc-by-nc-sa-4.0
task_categories:
- text-to-image
- image-to-image
language:
- en
tags:
- southpark
- cartoon
- animation
- comedy
- images
- frames
pretty_name: southpark
size_categories:
- 100K<n<1M
---
# South Park
## South Park Images Dataset
***
***
# Installation
```python
from huggingface_hub import snapshot_download
repo_id = "asigalov61/South-Park"
repo_type = 'dataset'
local_dir = "./South-Park"
snapshot_download(repo_id, repo_type=repo_type, local_dir=local_dir)
```
***
# Make your own dataset
```sh
!pip install opencv-python
```
```python
import cv2
import os
from tqdm import tqdm
#===============================================================================================
def scan_videos(directory, videos_extensions=['.mkv', '.mp4', '.avi']):
video_files = [os.path.join(directory, f) for f in os.listdir(directory) if os.path.splitext(f)[1].lower() in videos_extensions]
return video_files
def extract_frames(video_path,
output_folder,
interval=0.1,
square_size=480,
scale_size=128,
images_ext='.jpg'
):
if not os.path.exists(output_folder):
os.makedirs(output_folder)
cap = cv2.VideoCapture(video_path)
fps = cap.get(cv2.CAP_PROP_FPS)
frame_interval = int(fps * interval)
frame_count = 0
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
print('Video file:', os.path.basename(video_path))
with tqdm(total=total_frames, desc='Extracting frames') as pbar:
while True:
ret, frame = cap.read()
if not ret:
break
if frame_count % frame_interval == 0:
# Calculate the coordinates for cropping the center square
height, width = frame.shape[:2]
center_y, center_x = height // 2, width // 2
half_size = square_size // 2
top_left_x = max(center_x - half_size, 0)
top_left_y = max(center_y - half_size, 0)
bottom_right_x = min(center_x + half_size, width)
bottom_right_y = min(center_y + half_size, height)
square_frame = frame[top_left_y:bottom_right_y, top_left_x:bottom_right_x]
# Normalize brightness and contrast
normalized_frame = cv2.normalize(square_frame, None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX)
# Resize
resized_frame = cv2.resize(normalized_frame, (scale_size, scale_size))
frame_name = os.path.join(output_folder, f"frame_{frame_count}{images_ext}")
cv2.imwrite(frame_name, resized_frame)
frame_count += 1
pbar.update(1)
cap.release()
print(f"Frames extracted to {output_folder}")
#===============================================================================================
videos_dir = 'Videos'
videos_extensions = ['.mkv', '.mp4', '.avi']
frames_output_dir = 'Output'
frames_extraction_interval = 0.1 # FPS * frames_extraction_interval
original_frame_size = 480
final_frame_size = 128
output_frames_extension = '.jpg'
#===============================================================================================
print('=' * 70)
print('Scanning videos dir...')
video_files = scan_videos(videos_dir)
print('Done!')
print('=' * 70)
print('Found', len(video_files), 'video files')
print('=' * 70)
print('Starting extraction...')
print('=' * 70)
for video in video_files:
extract_frames(video,
os.path.join(frames_output_dir, os.path.splitext(os.path.basename(video))[0]),
frames_extraction_interval,
original_frame_size,
final_frame_size,
output_frames_extension
)
print('=' * 70)
print('Extraction finished!')
print('=' * 70)
print('Scanning for extracted frames...')
frames_list = list()
for (dirpath, dirnames, filenames) in os.walk(frames_output_dir):
frames_list += [os.path.join(dirpath, file) for file in filenames if file.endswith(output_frames_extension)]
print('Done!')
print('=' * 70)
print('Found', len(frames_list), 'video frames')
print('=' * 70)
print('Done!')
print('=' * 70)
```
***
### Project Los Angeles
### Tegridy Code 2024 |