import matplotlib.pyplot as plt import cv2 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") if not os.path.exists(output_dir): os.makedirs(output_dir) data = [] append = (file != 1) for n in num_objects_list: max_obj = 2*n 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(-0.1, 1.1) plt.ylim(-0.1, 1.1) # Generate random positions for the shapes positions = [] radius = 0.05 shapes = ['circle', 'triangle', 'rectangle', 'pentagon'] colours = ['red', 'green', 'blue', 'yellow', 'orange', 'black'] for i in range(n): while True: x, y = random.uniform(0.1, 0.9), random.uniform(0.1, 0.9) # Ensure shapes don't overlap if all(((x - px) ** 2 + (y - py) ** 2) ** 0.5 > 2 * radius for px, py in positions): positions.append((x, y)) break # Choose one odd-colored shape #odd_index = random.randint(0, n - 1) # Draw shapes and label them for i, (x, y) in enumerate(positions): color = random.choice(colours) shape_type = random.choice(shapes) if shape_type == 'circle': shape = plt.Circle((x, y), radius, color=color) elif shape_type == 'triangle': triangle = np.array([[x, y + radius], [x - radius, y - radius], [x + radius, y - radius]]) shape = plt.Polygon(triangle, color=color) elif shape_type == 'rectangle': shape = plt.Rectangle((x - radius, y - radius), 2 * radius, 2 * radius, color=color) elif shape_type == 'pentagon': pentagon = np.array([ [x, y + radius], [x + 0.95 * radius, y + 0.31 * radius], [x + 0.59 * radius, y - 0.81 * radius], [x - 0.59 * radius, y - 0.81 * radius], [x - 0.95 * radius, y + 0.31 * radius] ]) shape = plt.Polygon(pentagon, color=color) 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 fig, ax = plt.subplots() ax.set_aspect('equal') plt.axis('off') # Adjust plot limits to prevent cutoff plt.xlim(-203.5, 203.5) plt.ylim(-203.5, 203.5) # Generate random positions for the shapes positions = [] radius = 3.5 shapes = ['circle', 'triangle', 'rectangle', 'pentagon'] colours = ['red', 'green', 'blue', 'yellow', 'orange', 'black'] for i in range(max_obj): while True: x, y = random.uniform(-200, -3.5), random.uniform(-200, 200) # Ensure shapes don't overlap if all(((x - px) ** 2 + (y - py) ** 2) ** 0.5 > 2 * radius for px, py in positions): positions.append((x, y)) break # Choose one odd-colored shape #odd_index = random.randint(0, n - 1) # Draw shapes and label them color, shape_type = [], [] plt.axvline(x = 0, color = 'blue') for i, (x, y) in enumerate(positions): color.append(random.choice(colours)) shape_type.append(random.choice(shapes)) if shape_type[-1] == 'circle': shape = plt.Circle((x, y), radius, color=color[-1]) elif shape_type[-1] == 'triangle': triangle = np.array([[x, y + radius], [x - radius, y - radius], [x + radius, y - radius]]) shape = plt.Polygon(triangle, color=color[-1]) elif shape_type[-1] == 'rectangle': shape = plt.Rectangle((x - radius, y - radius), 2 * radius, 2 * radius, color=color[-1]) elif shape_type[-1] == 'pentagon': pentagon = np.array([ [x, y + radius], [x + 0.95 * radius, y + 0.31 * radius], [x + 0.59 * radius, y - 0.81 * radius], [x - 0.59 * radius, y - 0.81 * radius], [x - 0.95 * radius, y + 0.31 * radius] ]) shape = plt.Polygon(pentagon, color=color[-1]) ax.add_patch(shape) filename = f"first{file}.png" filepath = os.path.join(output_dir, filename) plt.savefig(filepath, bbox_inches='tight') plt.close() fig, ax = plt.subplots() ax.set_aspect('equal') plt.axis('off') # Adjust plot limits to prevent cutoff plt.xlim(-203.5, 203.5) plt.ylim(-203.5, 203.5) for i in range(n): x = list(positions[i]) x[0] = -x[0] positions[i] = tuple(x) plt.axvline(x = 0, color = 'blue') for i, (x, y) in enumerate(positions): if shape_type[i] == 'circle': shape = plt.Circle((x, y), radius, color=color[i]) elif shape_type[i] == 'triangle': triangle = np.array([[x, y + radius], [x - radius, y - radius], [x + radius, y - radius]]) shape = plt.Polygon(triangle, color=color[i]) elif shape_type[i] == 'rectangle': shape = plt.Rectangle((x - radius, y - radius), 2 * radius, 2 * radius, color=color[i]) elif shape_type[i] == 'pentagon': pentagon = np.array([ [x, y + radius], [x + 0.95 * radius, y + 0.31 * radius], [x + 0.59 * radius, y - 0.81 * radius], [x - 0.59 * radius, y - 0.81 * radius], [x - 0.95 * radius, y + 0.31 * radius] ]) shape = plt.Polygon(pentagon, color=color[i]) ax.add_patch(shape) filename = f"second{file}.png" file += 1 filepath = os.path.join(output_dir, filename) plt.savefig(filepath, bbox_inches='tight') plt.close() gold_answer = n """if choice == 0: img = cv2.imread(filepath) img_mirror = np.flip(img, axis=1) cv2.imwrite(os.path.join(output_dir, f"second{file-1}.png"), img_mirror) gold_answer = "Yes" else: angles = [90, 180, 270, 360] angle = random.choice(angles) img = Image.open(filepath) rotated_image = img.rotate(angle, PIL.Image.BILINEAR) rotated_image.save(os.path.join(output_dir, f"second{file-1}.png"), "PNG") gold_answer = "No" """ gold_output = { "id": filename, "mirror_image": gold_answer, "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)