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feat: beauty brightness sharpen contrast (#127)

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* finish

* add contrast

* add sharpen
This commit is contained in:
Ze-Yi LIN
2024-09-15 02:45:37 +08:00
committed by GitHub
parent 56762d8519
commit e6d8bee27b
8 changed files with 281 additions and 39 deletions
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demo/locals.py
+42
View File
@@ -564,4 +564,46 @@ LOCALES = {
"label": "미백 강도",
},
},
"brightness_strength": {
"en": {
"label": "brightness strength",
},
"zh": {
"label": "亮度强度",
},
"ja": {
"label": "明るさの強さ",
},
"ko": {
"label": "밝기 강도",
},
},
"contrast_strength": {
"en": {
"label": "contrast strength",
},
"zh": {
"label": "对比度强度",
},
"ja": {
"label": "コントラスト強度",
},
"ko": {
"label": "대비 강도",
},
},
"sharpen_strength": {
"en": {
"label": "sharpen strength",
},
"zh": {
"label": "锐化强度",
},
"ja": {
"label": "シャープ化強度",
},
"ko": {
"label": "샤ープ 강도",
},
},
}
demo/processor.py
+13 -1
View File
@@ -49,6 +49,9 @@ class IDPhotoProcessor:
whitening_strength=0,
image_dpi_option=False,
custom_image_dpi=None,
brightness_strength=0,
contrast_strength=0,
sharpen_strength=0,
):
# 初始化参数
top_distance_min = top_distance_max - 0.02
@@ -103,6 +106,9 @@ class IDPhotoProcessor:
top_distance_max,
top_distance_min,
whitening_strength,
brightness_strength,
contrast_strength,
sharpen_strength,
)
except (FaceError, APIError):
return self._handle_photo_generation_error(language)
@@ -185,7 +191,7 @@ class IDPhotoProcessor:
def _generate_id_photo(
self,
creator,
creator: IDCreator,
input_image,
idphoto_json,
language,
@@ -193,6 +199,9 @@ class IDPhotoProcessor:
top_distance_max,
top_distance_min,
whitening_strength,
brightness_strength,
contrast_strength,
sharpen_strength,
):
"""生成证件照"""
change_bg_only = (
@@ -205,6 +214,9 @@ class IDPhotoProcessor:
head_measure_ratio=head_measure_ratio,
head_top_range=(top_distance_max, top_distance_min),
whitening_strength=whitening_strength,
brightness_strength=brightness_strength,
contrast_strength=contrast_strength,
sharpen_strength=sharpen_strength,
)
def _handle_photo_generation_error(self, language):
demo/ui.py
+45
View File
@@ -160,6 +160,7 @@ def create_ui(
with gr.Tab(
LOCALES["beauty_tab"][DEFAULT_LANG]["label"]
) as beauty_parameter_tab:
# 美白组件
whitening_option = gr.Slider(
label=LOCALES["whitening_strength"][DEFAULT_LANG]["label"],
minimum=0,
@@ -169,6 +170,35 @@ def create_ui(
interactive=True,
)
with gr.Row():
# 亮度组件
brightness_option = gr.Slider(
label=LOCALES["brightness_strength"][DEFAULT_LANG]["label"],
minimum=-5,
maximum=25,
value=0,
step=1,
interactive=True,
)
# 对比度组件
contrast_option = gr.Slider(
label=LOCALES["contrast_strength"][DEFAULT_LANG]["label"],
minimum=-10,
maximum=50,
value=0,
step=1,
interactive=True,
)
# 锐化组件
sharpen_option = gr.Slider(
label=LOCALES["sharpen_strength"][DEFAULT_LANG]["label"],
minimum=0,
maximum=5,
value=0,
step=1,
interactive=True,
)
# TAB4 - 水印
with gr.Tab(
LOCALES["watermark_tab"][DEFAULT_LANG]["label"]
@@ -431,6 +461,15 @@ def create_ui(
custom_image_dpi_size: gr.update(
label=LOCALES["image_dpi"][language]["label"]
),
brightness_option: gr.update(
label=LOCALES["brightness_strength"][language]["label"]
),
contrast_option: gr.update(
label=LOCALES["contrast_strength"][language]["label"]
),
sharpen_option: gr.update(
label=LOCALES["sharpen_strength"][language]["label"]
),
}
def change_color(colors, lang):
@@ -507,6 +546,9 @@ def create_ui(
whitening_option,
image_dpi_options,
custom_image_dpi_size,
brightness_option,
contrast_option,
sharpen_option,
],
)
@@ -564,6 +606,9 @@ def create_ui(
whitening_option,
image_dpi_options,
custom_image_dpi_size,
brightness_option,
contrast_option,
sharpen_option,
],
outputs=[
img_output_standard,
hivision/creator/__init__.py
+9 -2
View File
@@ -45,7 +45,6 @@ class IDCreator:
self.matting_handler: ContextHandler = extract_human
self.detection_handler: ContextHandler = detect_face_mtcnn
self.beauty_handler: ContextHandler = beauty_face
# 上下文
self.ctx = None
@@ -60,6 +59,9 @@ class IDCreator:
head_top_range: float = (0.12, 0.1),
face: Tuple[int, int, int, int] = None,
whitening_strength: int = 0,
brightness_strength: int = 0,
contrast_strength: int = 0,
sharpen_strength: int = 0,
) -> Result:
"""
证件照处理函数
@@ -72,7 +74,9 @@ class IDCreator:
:param head_top_range: 头距离顶部的比例（max,min)
:param face: 人脸坐标
:param whitening_strength: 美白强度
:param brightness_strength: 亮度强度
:param contrast_strength: 对比度强度
:param sharpen_strength: 锐化强度
:return: 返回处理后的证件照和一系列参数
"""
# 0.初始化上下文
@@ -85,6 +89,9 @@ class IDCreator:
crop_only=crop_only,
face=face,
whitening_strength=whitening_strength,
brightness_strength=brightness_strength,
contrast_strength=contrast_strength,
sharpen_strength=sharpen_strength,
)
self.ctx = Context(params)
hivision/creator/context.py
+18
View File
@@ -22,6 +22,9 @@ class Params:
head_top_range: float = (0.12, 0.1),
face: Tuple[int, int, int, int] = None,
whitening_strength: int = 0,
brightness_strength: int = 0,
contrast_strength: int = 0,
sharpen_strength: int = 0,
):
self.__size = size
self.__change_bg_only = change_bg_only
@@ -31,6 +34,9 @@ class Params:
self.__head_top_range = head_top_range
self.__face = face
self.__whitening_strength = whitening_strength
self.__brightness_strength = brightness_strength
self.__contrast_strength = contrast_strength
self.__sharpen_strength = sharpen_strength
@property
def size(self):
@@ -64,6 +70,18 @@ class Params:
def whitening_strength(self):
return self.__whitening_strength
@property
def brightness_strength(self):
return self.__brightness_strength
@property
def contrast_strength(self):
return self.__contrast_strength
@property
def sharpen_strength(self):
return self.__sharpen_strength
class Result:
def __init__(
hivision/plugin/beauty/base_adjust.py
+121
View File
@@ -0,0 +1,121 @@
"""
亮度、对比度、锐化调整模块
"""
import cv2
import numpy as np
def adjust_brightness_contrast_sharpen(
image,
brightness_factor=0,
contrast_factor=0,
sharpen_strength=0,
):
"""
调整图像的亮度和对比度。
参数:
image (numpy.ndarray): 输入的图像数组。
brightness_factor (float): 亮度调整因子。大于0增加亮度，小于0降低亮度。
contrast_factor (float): 对比度调整因子。大于0增加对比度，小于0降低对比度。
返回:
numpy.ndarray: 调整亮度和对比度后的图像。
"""
if brightness_factor == 0 and contrast_factor == 0 and sharpen_strength == 0:
return image.copy()
adjusted_image = image.copy()
# 将亮度因子转换为调整值
alpha = 1.0 + (contrast_factor / 100.0)
beta = brightness_factor
# 使用 cv2.convertScaleAbs 函数调整亮度和对比度
adjusted_image = cv2.convertScaleAbs(adjusted_image, alpha=alpha, beta=beta)
# 增强锐化
adjusted_image = sharpen_image(adjusted_image, sharpen_strength)
return adjusted_image
def sharpen_image(image, strength=0):
"""
对图像进行锐化处理。
参数:
image (numpy.ndarray): 输入的图像数组。
strength (float): 锐化强度，范围建议为0-5。0表示不进行锐化。
返回:
numpy.ndarray: 锐化后的图像。
"""
print(f"Shapen strength: {strength}")
if strength == 0:
return image.copy()
strength = strength * 20
# 将强度转换为适合kernel的值，但减小影响
kernel_strength = 1 + (strength / 500) # 将除数从100改为500，减小锐化效果
# 创建更温和的锐化kernel
kernel = (
np.array([[-0.5, -0.5, -0.5], [-0.5, 5, -0.5], [-0.5, -0.5, -0.5]])
* kernel_strength
)
# 应用锐化kernel
sharpened = cv2.filter2D(image, -1, kernel)
# 确保结果在0-255范围内
sharpened = np.clip(sharpened, 0, 255).astype(np.uint8)
# 混合原图和锐化后的图像，进一步减小锐化效果
alpha = strength / 200 # 混合比例，最大为0.5
blended = cv2.addWeighted(image, 1 - alpha, sharpened, alpha, 0)
return blended
# Gradio接口
def base_adjustment(image, brightness, contrast, sharpen):
adjusted = adjust_brightness_contrast_sharpen(image, brightness, contrast, sharpen)
return adjusted
if __name__ == "__main__":
import gradio as gr
iface = gr.Interface(
fn=base_adjustment,
inputs=[
gr.Image(label="Input Image", height=400),
gr.Slider(
minimum=-20,
maximum=20,
value=0, # Changed from 'default' to 'value'
step=1,
label="Brightness",
),
gr.Slider(
minimum=-100,
maximum=100,
value=0,
step=1,
label="Contrast",
),
gr.Slider(
minimum=0,
maximum=5,
value=0,
step=1,
label="Sharpen",
),
],
outputs=gr.Image(label="Adjusted Image"),
title="Image Brightness Adjustment",
description="Adjust the brightness of an image using a slider.",
)
iface.launch()
hivision/plugin/beauty/brightness.py
-31
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@@ -1,31 +0,0 @@
import cv2
import numpy as np
def adjust_brightness(image, brightness_factor):
"""
调整图像的亮度。
参数:
image (numpy.ndarray): 输入的图像数组。
brightness_factor (float): 亮度调整因子。大于1增加亮度，小于1降低亮度。
返回:
numpy.ndarray: 调整亮度后的图像。
"""
# 将图像转换为HSV颜色空间
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
# 分离HSV通道
h, s, v = cv2.split(hsv)
# 调整V通道（亮度）
v = np.clip(v * brightness_factor, 0, 255).astype(np.uint8)
# 合并通道
hsv = cv2.merge((h, s, v))
# 转换回BGR颜色空间
adjusted = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
return adjusted
hivision/plugin/beauty/handler.py
+33 -5
View File
@@ -1,19 +1,47 @@
import cv2
import numpy as np
from hivision.creator.context import Context
from hivision.plugin.beauty.whitening import make_whitening
from hivision.plugin.beauty.base_adjust import adjust_brightness_contrast_sharpen
def beauty_face(ctx: Context):
"""
对人脸进行美颜处理
1. 美白
2. 亮度
:param ctx: Context对象，包含处理参数和图像
"""
# 目前只实现了美白功能，可以在这里添加其他美颜处理
middle_image = ctx.origin_image.copy()
processed = False
# 如果美白强度大于0，进行美白处理
if ctx.params.whitening_strength > 0:
_, _, _, alpha = cv2.split(ctx.matting_image)
b, g, r = cv2.split(
make_whitening(ctx.origin_image, ctx.params.whitening_strength)
middle_image = make_whitening(middle_image, ctx.params.whitening_strength)
processed = True
# 如果亮度、对比度、锐化强度不为0，进行亮度、对比度、锐化处理
if (
ctx.params.brightness_strength != 0
or ctx.params.contrast_strength != 0
or ctx.params.sharpen_strength != 0
):
print(
f"Brightness strength: {ctx.params.brightness_strength}, Contrast strength: {ctx.params.contrast_strength}, Sharpen strength: {ctx.params.sharpen_strength}"
)
middle_image = adjust_brightness_contrast_sharpen(
middle_image,
ctx.params.brightness_strength,
ctx.params.contrast_strength,
ctx.params.sharpen_strength,
)
processed = True
# 如果进行了美颜处理，更新matting_image
if processed:
# 分离中间图像的BGR通道
b, g, r = cv2.split(middle_image)
# 从原始matting_image中获取alpha通道
_, _, _, alpha = cv2.split(ctx.matting_image)
# 合并处理后的BGR通道和原始alpha通道
ctx.matting_image = cv2.merge((b, g, r, alpha))