Datasets:

aggr8
/

Percept-V

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 = []
    #max_obj = 30
    append = (file != 1)

    for n in num_objects_list:
        max_obj = n*2
        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, 1500)
            plt.ylim(-1000, 1000)

            # Generate random positions for the shapes
            positions = []
            radius = 75
            shapes = ['triangle', 'rectangle', 'pentagon']
            colours = ['red', 'green', 'blue']
            height, width = 1000, 1500
            gold_answer = set()
            for i in range(max_obj):
                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):
                        positions.append((x, y))
                        break

            # Choose one odd-colored shape
            #odd_index = random.randint(0, n - 1)

            # Draw shapes and label them
            circle, tri, rect, pent = [], [], [], []
            shape_types = []
            for _ in range(max_obj):
                shape_types.append(random.choice(shapes))
            indices = random.sample(range(0, max_obj), n)
            for index in indices:
                shape_types[index] = 'circle'

            for i, (x, y) in enumerate(positions):
                color = random.choice(colours)
                shape_type = shape_types[i]

                if shape_type == 'circle':
                    shape = plt.Circle((x, y), radius, color=color)
                    circle.append(str(i+1))
                elif shape_type == 'triangle':
                    triangle = np.array([[x, y + radius], [x - radius, y - radius], [x + radius, y - radius]])
                    shape = plt.Polygon(triangle, color=color)
                    tri.append(str(i+1))
                elif shape_type == 'rectangle':
                    shape = plt.Rectangle((x - radius, y - radius), 2 * radius, 2 * radius, color=color)
                    rect.append(str(i+1))
                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)
                    pent.append(str(i+1))

                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()

            gold_output = {
                "id": filename,
                "circles": sorted(circle),
                "triangles": sorted(tri),
                "rectangles": sorted(rect),
                "pentagons": sorted(pent),
                "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)

	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 = []
	#max_obj = 30
	append = (file != 1)

	for n in num_objects_list:
	max_obj = n*2
	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, 1500)
	plt.ylim(-1000, 1000)

	# Generate random positions for the shapes
	positions = []
	radius = 75
	shapes = ['triangle', 'rectangle', 'pentagon']
	colours = ['red', 'green', 'blue']
	height, width = 1000, 1500
	gold_answer = set()
	for i in range(max_obj):
	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):
	positions.append((x, y))
	break

	# Choose one odd-colored shape
	#odd_index = random.randint(0, n - 1)

	# Draw shapes and label them
	circle, tri, rect, pent = [], [], [], []
	shape_types = []
	for _ in range(max_obj):
	shape_types.append(random.choice(shapes))
	indices = random.sample(range(0, max_obj), n)
	for index in indices:
	shape_types[index] = 'circle'

	for i, (x, y) in enumerate(positions):
	color = random.choice(colours)
	shape_type = shape_types[i]

	if shape_type == 'circle':
	shape = plt.Circle((x, y), radius, color=color)
	circle.append(str(i+1))
	elif shape_type == 'triangle':
	triangle = np.array([[x, y + radius], [x - radius, y - radius], [x + radius, y - radius]])
	shape = plt.Polygon(triangle, color=color)
	tri.append(str(i+1))
	elif shape_type == 'rectangle':
	shape = plt.Rectangle((x - radius, y - radius), 2 * radius, 2 * radius, color=color)
	rect.append(str(i+1))
	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)
	pent.append(str(i+1))

	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()

	gold_output = {
	"id": filename,
	"circles": sorted(circle),
	"triangles": sorted(tri),
	"rectangles": sorted(rect),
	"pentagons": sorted(pent),
	"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)