Datasets:

Obedience-Violin
/

Violin

import json

from PIL import Image
import cv2
import numpy as np
import random
import os

JSON_PATH = os.path.join('metadata', 'mapping_file.json')
BASE_OUT_DIR = os.path.join('data', 'Task_Image_Mask_raw_image')
RANDOM_DIR = os.path.join(BASE_OUT_DIR, 'random_mask')

os.makedirs(RANDOM_DIR, exist_ok=True)
def generate_random_mask(shape=(512, 512), min_area_ratio=0.03, max_area_ratio=0.3):
    """
    Generates a random geometric mask where the shape interior is BLACK (0) 
    and the background is WHITE (255).
    """
    h, w = shape
    total_area = h * w
    
    # Target area for the shape (the black part)
    target_area = random.uniform(total_area * min_area_ratio, total_area * max_area_ratio)
    
    # Pick a random shape type
    shape_type = random.choice(["rectangle", "triangle", "ellipse"])
    
    # Initialize with 255 (White - Area to keep)
    mask = np.full((h, w), 255, dtype=np.uint8)
    
    if shape_type == "rectangle":
        aspect = random.uniform(0.5, 2.0)
        sw = int(np.sqrt(target_area * aspect))
        sh = int(target_area / sw)
        radius = int(np.sqrt(sw**2 + sh**2) / 2) + 5
        
        cx, cy = get_safe_center(h, w, radius)
        angle = random.randint(0, 180)
        rect = ((cx, cy), (sw, sh), angle)
        box = cv2.boxPoints(rect)
        # Draw the shape in 0 (Black - Area to modify)
        cv2.fillPoly(mask, [np.int0(box)], 0)

    elif shape_type == "ellipse":
        aspect = random.uniform(0.5, 2.0)
        semi_a = int(np.sqrt((target_area / np.pi) * aspect))
        semi_b = int((target_area / np.pi) / semi_a)
        radius = max(semi_a, semi_b) + 5
        
        cx, cy = get_safe_center(h, w, radius)
        angle = random.randint(0, 360)
        cv2.ellipse(mask, (cx, cy), (semi_a, semi_b), angle, 0, 360, 0, -1)

    elif shape_type == "triangle":
        # Using circumradius to control area: 
        R = int(np.sqrt(target_area / 1.299))
        # R = int(np.sqrt(target_area / 1.0)) 
        radius = R + 5
        cx, cy = get_safe_center(h, w, radius)
        
        base_angles = [0, 120, 240]
        angles = [np.deg2rad(a + random.randint(-25, 25)) for a in base_angles]
        
        pts = np.array([
            [cx + R * np.cos(a), cy + R * np.sin(a)] for a in angles
        ], np.int32)
        cv2.fillPoly(mask, [pts], 0)

    return mask

def get_safe_center(h, w, radius):
    """
    Returns a random (cx, cy) that ensures a circle of 'radius' fits in the image.
    """
    pad = radius + 5
    # Defensive check if radius is too large for the image
    safe_h = max(pad, h - pad)
    safe_w = max(pad, w - pad)
    
    cx = random.randint(min(pad, safe_w), max(pad, safe_w))
    cy = random.randint(min(pad, safe_h), max(pad, safe_h))
    return cx, cy




def main():
    if not os.path.exists(JSON_PATH):
        print(f"Error: {JSON_PATH} not found.")
        return

    print(f"Loading metadata...")
    with open(JSON_PATH, 'r', encoding='utf-8') as f:
        data = json.load(f)

    count = 0
    for img_id, info in data.items():
        # Get dimensions if available, else default to 512
        h = info.get('height', 512)
        w = info.get('width', 512)
        img_shape = (h, w)

        # 3. Generate a brand new Random Mask
        rand_mask = generate_random_mask(shape=img_shape)
        cv2.imwrite(os.path.join(RANDOM_DIR, f"{img_id}.png"), rand_mask)

        count += 1
        if count % 100 == 0:
            print(f"Processed {count} images...")
            

    print(f"\nDone! Successfully processed {count} samples.")

if __name__ == "__main__":
    random.seed(42)
    main()

	import json

	from PIL import Image
	import cv2
	import numpy as np
	import random
	import os

	JSON_PATH = os.path.join('metadata', 'mapping_file.json')
	BASE_OUT_DIR = os.path.join('data', 'Task_Image_Mask_raw_image')
	RANDOM_DIR = os.path.join(BASE_OUT_DIR, 'random_mask')

	os.makedirs(RANDOM_DIR, exist_ok=True)
	def generate_random_mask(shape=(512, 512), min_area_ratio=0.03, max_area_ratio=0.3):
	"""
	Generates a random geometric mask where the shape interior is BLACK (0)
	and the background is WHITE (255).
	"""
	h, w = shape
	total_area = h * w

	# Target area for the shape (the black part)
	target_area = random.uniform(total_area * min_area_ratio, total_area * max_area_ratio)

	# Pick a random shape type
	shape_type = random.choice(["rectangle", "triangle", "ellipse"])

	# Initialize with 255 (White - Area to keep)
	mask = np.full((h, w), 255, dtype=np.uint8)

	if shape_type == "rectangle":
	aspect = random.uniform(0.5, 2.0)
	sw = int(np.sqrt(target_area * aspect))
	sh = int(target_area / sw)
	radius = int(np.sqrt(sw2 + sh2) / 2) + 5

	cx, cy = get_safe_center(h, w, radius)
	angle = random.randint(0, 180)
	rect = ((cx, cy), (sw, sh), angle)
	box = cv2.boxPoints(rect)
	# Draw the shape in 0 (Black - Area to modify)
	cv2.fillPoly(mask, [np.int0(box)], 0)

	elif shape_type == "ellipse":
	aspect = random.uniform(0.5, 2.0)
	semi_a = int(np.sqrt((target_area / np.pi) * aspect))
	semi_b = int((target_area / np.pi) / semi_a)
	radius = max(semi_a, semi_b) + 5

	cx, cy = get_safe_center(h, w, radius)
	angle = random.randint(0, 360)
	cv2.ellipse(mask, (cx, cy), (semi_a, semi_b), angle, 0, 360, 0, -1)

	elif shape_type == "triangle":
	# Using circumradius to control area:
	R = int(np.sqrt(target_area / 1.299))
	# R = int(np.sqrt(target_area / 1.0))
	radius = R + 5
	cx, cy = get_safe_center(h, w, radius)

	base_angles = [0, 120, 240]
	angles = [np.deg2rad(a + random.randint(-25, 25)) for a in base_angles]

	pts = np.array([
	[cx + R * np.cos(a), cy + R * np.sin(a)] for a in angles
	], np.int32)
	cv2.fillPoly(mask, [pts], 0)

	return mask

	def get_safe_center(h, w, radius):
	"""
	Returns a random (cx, cy) that ensures a circle of 'radius' fits in the image.
	"""
	pad = radius + 5
	# Defensive check if radius is too large for the image
	safe_h = max(pad, h - pad)
	safe_w = max(pad, w - pad)

	cx = random.randint(min(pad, safe_w), max(pad, safe_w))
	cy = random.randint(min(pad, safe_h), max(pad, safe_h))
	return cx, cy




	def main():
	if not os.path.exists(JSON_PATH):
	print(f"Error: {JSON_PATH} not found.")
	return

	print(f"Loading metadata...")
	with open(JSON_PATH, 'r', encoding='utf-8') as f:
	data = json.load(f)

	count = 0
	for img_id, info in data.items():
	# Get dimensions if available, else default to 512
	h = info.get('height', 512)
	w = info.get('width', 512)
	img_shape = (h, w)

	# 3. Generate a brand new Random Mask
	rand_mask = generate_random_mask(shape=img_shape)
	cv2.imwrite(os.path.join(RANDOM_DIR, f"{img_id}.png"), rand_mask)

	count += 1
	if count % 100 == 0:
	print(f"Processed {count} images...")


	print(f"\nDone! Successfully processed {count} samples.")

	if __name__ == "__main__":
	random.seed(42)
	main()