Download inside_circles/script.py from aggr8/Percept-V: direct link, hf CLI and curl.
- Browser
- Download file 3.32 kB
-
https://huggingface.co/datasets/aggr8/Percept-V/resolve/main/inside_circles/script.py
- Command line
-
hf download hf://datasets/aggr8/Percept-V/inside_circles/script.py
-
curl -L -o script.py https://huggingface.co/datasets/aggr8/Percept-V/resolve/main/inside_circles/script.py
3.32 kB
| import matplotlib.pyplot as plt | |
| import PIL | |
| from PIL import Image | |
| import random | |
| import numpy as np | |
| import os | |
| import json | |
| import argparse | |
| def generate_shapes(num_images, num_objects_list , file): | |
| # Set up the plot | |
| output_dir = os.path.join(os.getcwd(), "data") | |
| input_dir = os.path.join(os.getcwd(), "background_image") | |
| if not os.path.exists(output_dir): | |
| os.makedirs(output_dir) | |
| data = [] | |
| append = (file != 1) | |
| for n in num_objects_list: | |
| for img_index in range(num_images): | |
| fig, ax = plt.subplots() | |
| ax.set_aspect('equal') | |
| plt.axis('off') | |
| # Adjust plot limits to prevent cutoff | |
| plt.xlim(-0.7, 1.4) | |
| plt.ylim(-0.7, 1.4) | |
| # Generate random positions for the shapes | |
| positions = [] | |
| radii = [] | |
| gold_answer = 0 | |
| for i in range(n): | |
| x, y = random.uniform(0.1, 0.9), random.uniform(0.1, 0.9) | |
| positions.append((x, y)) | |
| radius = random.uniform(0.1, 0.5) | |
| radii.append(radius) | |
| # Draw shapes and label them | |
| cx, cy = random.uniform(0.1, 0.9), random.uniform(0.1, 0.9) | |
| ax.add_patch(plt.Circle((cx, cy), 0.05, color='red')) | |
| for i, (x, y) in enumerate(positions): | |
| shape = plt.Circle((x, y), radii[i], color='black', fill=False) | |
| ax.add_patch(shape) | |
| if ((cx - x)**2 + (cy - y)**2)**0.5 < radii[i]: | |
| gold_answer += 1 | |
| # Save the plot to a file | |
| filename = f"{file}.png" | |
| file += 1 | |
| filepath = os.path.join(output_dir, filename) | |
| plt.savefig(filepath, bbox_inches='tight') | |
| plt.close() | |
| answer = False | |
| if gold_answer == 0: | |
| answer = False | |
| else: | |
| answer = True | |
| gold_output = { | |
| "id": filename, | |
| "inside_circles": answer, | |
| "num_circles": n | |
| } | |
| data.append(gold_output) | |
| if append: | |
| with open(os.path.join(os.getcwd() , "data.json"), "r") as f: | |
| old_data = json.load(f) | |
| old_data.extend(data) | |
| with open(os.path.join(os.getcwd() , "data.json"), "w") as f: | |
| json.dump(old_data, f, indent=2) | |
| else: | |
| with open(os.path.join(os.getcwd() , "data.json"), "w") as f: | |
| json.dump(data, f, indent=2) | |
| # # Example usage | |
| # generate_shapes(10, 'shapes.png') | |
| if __name__ == "__main__": | |
| # Parse command line arguments | |
| parser = argparse.ArgumentParser(description='Create an image of different objects') | |
| parser.add_argument( | |
| '--num_images', | |
| type=int, | |
| help='Number of images to generate', | |
| default=1 | |
| ) | |
| parser.add_argument( | |
| '--num_sizes', | |
| nargs='*', | |
| type=int, | |
| help='List of count of objects', | |
| default=[5] | |
| ) | |
| parser.add_argument( | |
| '--file', | |
| type=int, | |
| help='Starting file number', | |
| default=1 | |
| ) | |
| args = parser.parse_args() | |
| file = args.file | |
| num_object_list = args.num_sizes | |
| append = (file != 1) | |
| generate_shapes(args.num_images, num_object_list , file) | |