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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)
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