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import cv2 | |
import numpy as np | |
from typing import Dict, List | |
import colorsys | |
from pytoshop import layers | |
from pytoshop.enums import BlendMode | |
from pytoshop.core import PsdFile | |
def decode_to_mask(seg: np.ndarray[np.bool_]) -> np.ndarray[np.uint8]: | |
return seg.astype(np.uint8) * 255 | |
def generate_random_color(): | |
h = np.random.randint(0, 360) | |
s = np.random.randint(70, 100) / 100 | |
v = np.random.randint(70, 100) / 100 | |
r, g, b = colorsys.hsv_to_rgb(h/360, s, v) | |
return int(r * 255), int(g * 255), int(b * 255) | |
def create_base_layer(image: np.ndarray): | |
rgba_image = cv2.cvtColor(image, cv2.COLOR_RGB2RGBA) | |
return [rgba_image] | |
def create_mask_layers( | |
image: np.ndarray, | |
masks: List | |
): | |
layer_list = [] | |
sorted_masks = sorted(masks, key=lambda x: x['area'], reverse=True) | |
for info in sorted_masks: | |
rle = info['segmentation'] | |
mask = decode_to_mask(rle) | |
rgba_image = cv2.cvtColor(image, cv2.COLOR_RGB2RGBA) | |
rgba_image[..., 3] = cv2.bitwise_and(rgba_image[..., 3], rgba_image[..., 3], mask=mask) | |
layer_list.append(rgba_image) | |
return layer_list | |
def create_mask_gallery( | |
image: np.ndarray, | |
masks: List | |
): | |
mask_array_list = [] | |
label_list = [] | |
sorted_masks = sorted(masks, key=lambda x: x['area'], reverse=True) | |
for index, info in enumerate(sorted_masks): | |
rle = info['segmentation'] | |
mask = decode_to_mask(rle) | |
rgba_image = cv2.cvtColor(image, cv2.COLOR_RGB2RGBA) | |
rgba_image[..., 3] = cv2.bitwise_and(rgba_image[..., 3], rgba_image[..., 3], mask=mask) | |
mask_array_list.append(rgba_image) | |
label_list.append(f'Part {index}') | |
return [[img, label] for img, label in zip(mask_array_list, label_list)] | |
def create_mask_combined_images( | |
image: np.ndarray, | |
masks: List | |
): | |
final_result = np.zeros_like(image) | |
used_colors = set() | |
for info in masks: | |
rle = info['segmentation'] | |
mask = decode_to_mask(rle) | |
while True: | |
color = generate_random_color() | |
if color not in used_colors: | |
used_colors.add(color) | |
break | |
colored_mask = np.zeros_like(image) | |
colored_mask[mask > 0] = color | |
blended = cv2.addWeighted(image, 0.3, colored_mask, 0.7, 0) | |
final_result = np.where(mask[:, :, np.newaxis] > 0, blended, final_result) | |
combined_image = np.where(final_result != 0, final_result, image) | |
hsv = cv2.cvtColor(combined_image, cv2.COLOR_BGR2HSV) | |
hsv[:, :, 1] = np.clip(hsv[:, :, 1] * 1.5, 0, 255) | |
enhanced = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) | |
return [enhanced, "Masked"] | |
def insert_psd_layer( | |
psd: PsdFile, | |
image_data: np.ndarray, | |
layer_name: str, | |
blending_mode: BlendMode | |
): | |
channel_data = [layers.ChannelImageData(image=image_data[:, :, i], compression=1) for i in range(4)] | |
layer_record = layers.LayerRecord( | |
channels={-1: channel_data[3], 0: channel_data[0], 1: channel_data[1], 2: channel_data[2]}, | |
top=0, bottom=image_data.shape[0], left=0, right=image_data.shape[1], | |
blend_mode=blending_mode, | |
name=layer_name, | |
opacity=255, | |
) | |
psd.layer_and_mask_info.layer_info.layer_records.append(layer_record) | |
return psd | |
def save_psd( | |
input_image_data: np.ndarray, | |
layer_data: List, | |
layer_names: List, | |
blending_modes: List, | |
output_path: str | |
): | |
psd_file = PsdFile(num_channels=3, height=input_image_data.shape[0], width=input_image_data.shape[1]) | |
psd_file.layer_and_mask_info.layer_info.layer_records.clear() | |
for index, layer in enumerate(layer_data): | |
psd_file = insert_psd_layer(psd_file, layer, layer_names[index], blending_modes[index]) | |
with open(output_path, 'wb') as output_file: | |
psd_file.write(output_file) | |
def save_psd_with_masks( | |
image: np.ndarray, | |
masks: List, | |
output_path: str | |
): | |
original_layer = create_base_layer(image) | |
mask_layers = create_mask_layers(image, masks) | |
names = [f'Part {i}' for i in range(len(mask_layers))] | |
modes = [BlendMode.normal] * (len(mask_layers)+1) | |
save_psd(image, original_layer+mask_layers, ['Original_Image']+names, modes, output_path) | |