Download circle_location/script.py from aggr8/Percept-V: direct link, hf CLI and curl.
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https://huggingface.co/datasets/aggr8/Percept-V/resolve/main/circle_location/script.py
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hf download hf://datasets/aggr8/Percept-V/circle_location/script.py
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curl -L -o script.py https://huggingface.co/datasets/aggr8/Percept-V/resolve/main/circle_location/script.py
4.07 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): | |
| #im = Image.open(os.path.join(input_dir, f"bg_{img_index+1}.png")) | |
| fig, ax = plt.subplots() | |
| #ax.imshow(im) | |
| ax.set_aspect('equal') | |
| plt.axis('off') | |
| # Adjust plot limits to prevent cutoff | |
| plt.xlim(-1500.0, 1500.0) | |
| plt.ylim(-1000, 1000) | |
| # Generate random positions for the shapes | |
| positions = [] | |
| radius = 75 | |
| height, width = 1000, 1500 | |
| for i in range(n): | |
| while True: | |
| x, y = random.randint(-(width - radius), (width - radius)), random.randint(-(height - radius), (height-radius)) | |
| # Ensure shapes don't overlap | |
| if all(((x - px) ** 2 + (y - py) ** 2) ** 0.5 > 2 * radius for px, py in positions) and (abs(x) > radius and abs(y) > radius): | |
| positions.append((x, y)) | |
| break | |
| # Draw shapes and label them | |
| first, second, third, fourth = 0, 0, 0, 0 | |
| plt.axhline(0, color='black', linewidth=0.5) | |
| plt.axvline(0, color='black', linewidth=0.5) | |
| for i, (x, y) in enumerate(positions): | |
| #color = random.choice(colours) | |
| #shape_type = random.choice(shapes) | |
| if x>0 and y>0: | |
| first += 1 | |
| elif x<0 and y>0: | |
| second += 1 | |
| elif x<0 and y<0: | |
| third += 1 | |
| else: | |
| fourth += 1 | |
| shape = plt.Circle((x, y), radius, color='black') | |
| ax.add_patch(shape) | |
| #ax.text(x, y, str(i + 1), color='white', ha='center', va='center', fontsize=8, weight='bold') | |
| # 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() | |
| iterable = [first, second, third, fourth] | |
| answer = max(enumerate(iterable), key=lambda x: x[1])[0] + 1 | |
| gold_output = { | |
| "id": filename, | |
| "quadrant": answer, | |
| "count": iterable[answer-1], | |
| "num_objects": 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) | |