Spaces:
Running
Running
File size: 4,376 Bytes
f195437 dfc0c1a f195437 e00f944 3810a85 f195437 dfc0c1a f195437 e00f944 f195437 e00f944 f195437 e00f944 f195437 e00f944 f195437 e00f944 f195437 e00f944 f195437 dfc0c1a f195437 e00f944 f195437 dfc0c1a f195437 dfc0c1a f195437 dfc0c1a f195437 dfc0c1a f195437 e00f944 f195437 e00f944 f195437 e00f944 f195437 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 |
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]) -> np.ndarray[np.uint8]:
if isinstance(seg, np.ndarray) and seg.dtype == np.bool_:
return seg.astype(np.uint8) * 255
else:
return seg.astype(np.uint8)
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)
|