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Merge remote-tracking branch 'origin/main'

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Timothyxxx
2024-01-30 01:25:46 +08:00
parent 1756d3b672 e440b1cbba
commit 0a351eefdc
25 changed files with 1602 additions and 54 deletions
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19
desktop_env/evaluators/metrics/__init__.py
View File

@@ -22,10 +22,20 @@ from .slides import check_presenter_console_disable, check_image_stretch_and_cen
# from .table import check_sheet_list, check_xlsx_freeze, check_xlsx_zoom, check_data_validations
from .table import compare_table, compare_csv
from .thunderbird import check_thunderbird_prefs, check_thunderbird_filter
from .vlc import is_vlc_playing, is_vlc_recordings_folder, is_vlc_fullscreen, compare_images, compare_audios, \
compare_videos
from .thunderbird import check_thunderbird_prefs, check_thunderbird_filter
from .gimp import (
check_brightness_decrease_and_structure_sim,
check_contrast_increase_and_structure_sim,
check_saturation_increase_and_structure_sim,
check_image_size_and_structure_sim,
check_image_mirror,
check_palette_and_structure_sim,
check_textbox_on_leftside,
check_green_background,
check_file_exists_and_structure_sim,
check_triangle_position,
check_structure_sim,
check_config_status,
)
from .vlc import is_vlc_playing, is_vlc_recordings_folder, is_vlc_fullscreen, compare_images, compare_audios, \
compare_videos, check_qt_bgcone, check_one_instance_when_started_from_file, check_qt_minimal_view, \
check_qt_max_volume, \
@@ -33,4 +43,3 @@ from .vlc import is_vlc_playing, is_vlc_recordings_folder, is_vlc_fullscreen, co
from .vscode import compare_text_file, compare_config, compare_answer, is_extension_installed, check_json_settings, \
check_json_keybindings
from .basic_os import check_gnome_favorite_apps, is_utc_0, check_text_enlarged, check_moved_jpgs

365
desktop_env/evaluators/metrics/gimp.py
View File

@@ -1,8 +1,11 @@
import os
from typing import List, Union
from skimage.metrics import structural_similarity as ssim
from PIL import Image, ImageChops, ImageStat
def compare_images(pred_img_path_list: Union[str, List[str]], gold_img_path_list: Union[str, List[str]]) -> float:
def compare_images(pred_img_path_list: Union[str, List[str]],
gold_img_path_list: Union[str, List[str]]) -> float:
""" Compare two image lists, only if all images are the same, return 1.0, otherwise return 0.0
"""
if type(pred_img_path_list) != list:
@@ -36,11 +39,13 @@ def get_gimp_export_path():
# Handle the case where the configuration file is not found
print("GIMP configuration file not found")
return False
def check_file_exists(directory, filename):
file_path = os.path.join(directory, filename)
return 1 if os.path.isfile(file_path) else 0
def increase_saturation(image1_path: str, image2_path: str) -> float:
def calculate_saturation(image):
# convert the image to HSV mode
@@ -63,6 +68,7 @@ def increase_saturation(image1_path: str, image2_path: str) -> float:
return 1 if saturation1 < saturation2 else 0
def decrease_brightness(image1_path: str, image2_path: str) -> float:
def calculate_brightness(image):
# Convert the image to grayscale mode
@@ -81,9 +87,12 @@ def decrease_brightness(image1_path: str, image2_path: str) -> float:
brightness2 = calculate_brightness(image2)
return 1 if brightness1 > brightness2 else 0
import cv2
import numpy as np
def find_yellow_triangle(image):
# Convert the image to RGBA
rgba = cv2.cvtColor(image, cv2.COLOR_BGR2RGBA)
@@ -111,6 +120,7 @@ def find_yellow_triangle(image):
return cx, cy
def compare_triangle_positions(image1, image2):
image1 = cv2.imread(image1, cv2.IMREAD_COLOR)
image2 = cv2.imread(image2, cv2.IMREAD_COLOR)
@@ -119,16 +129,355 @@ def compare_triangle_positions(image1, image2):
cx2, cy2 = find_yellow_triangle(image2)
# calculate the distance between the center of the triangle and the center of the image
center_distance1 = np.sqrt((cx1 - image1.shape[1] // 2)**2 + (cy1 - image1.shape[0] // 2)**2)
center_distance2 = np.sqrt((cx2 - image2.shape[1] // 2)**2 + (cy2 - image2.shape[0] // 2)**2)
center_distance1 = np.sqrt(
(cx1 - image1.shape[1] // 2) ** 2 + (cy1 - image1.shape[0] // 2) ** 2)
center_distance2 = np.sqrt(
(cx2 - image2.shape[1] // 2) ** 2 + (cy2 - image2.shape[0] // 2) ** 2)
return 1 if center_distance1 > center_distance2 else 0
# Functions for the GIMP evaluator
def calculate_brightness(image):
"""Calculate the average brightness of an image"""
grayscale = image.convert('L')
stat = ImageStat.Stat(grayscale)
return stat.mean[0]
def normalize_brightness(image, target_brightness):
"""Normalize the brightness of an image to a target brightness in [0, 1]"""
current_brightness = calculate_brightness(image)
factor = target_brightness / current_brightness
# Apply a point transform to each pixel
def point_transform(x):
return min(255, max(0, int(x * factor)))
return image.point(point_transform)
def measure_saturation(hsv_image):
"""Measure the average saturation of an image"""
# Split into H, S, V channels
_, s, _ = hsv_image.split()
# Convert the saturation channel to a numpy array
s_array = np.array(s)
# Calculate the average saturation
avg_saturation = np.mean(s_array)
return avg_saturation
def calculate_contrast(image):
"""Calculate the contrast of an image as the standard deviation of the pixel
values."""
pixels = np.asarray(image, dtype=np.float32)
return np.std(pixels)
def structure_check_by_mse(img1, img2, threshold=0.03):
"""Check if two images are approximately the same by MSE"""
mse = np.mean(
(np.array(img1, dtype=np.float32) / 255
- np.array(img2, dtype=np.float32) / 255) ** 2)
structure_same = True if mse < threshold else False
print("MSE: ", mse)
return structure_same
def structure_check_by_ssim(img1, img2, threshold=0.9):
"""Check if two images are approximately the same by SSIM"""
similarity = ssim(np.array(img1), np.array(img2), multichannel=True)
print("SSIM: ", similarity)
return similarity >= threshold
def check_brightness_decrease_and_structure_sim(src_path, tgt_path):
"""
Check the brightness of src is lower than tgt and the structures are similar
gimp:7a4deb26-d57d-4ea9-9a73-630f66a7b568
"""
img_src = Image.open(src_path)
img_tgt = Image.open(tgt_path)
# Brightness comparison
brightness_src = calculate_brightness(img_src)
brightness_tgt = calculate_brightness(img_tgt)
brightness_reduced = brightness_tgt > brightness_src
# Normalize and compare images
target_brightness = 128
img_src_normalized = normalize_brightness(img_src, target_brightness)
img_tgt_normalized = normalize_brightness(img_tgt, target_brightness)
structure_same = structure_check_by_mse(img_src_normalized, img_tgt_normalized)
return brightness_reduced and structure_same
def check_saturation_increase_and_structure_sim(src_path, tgt_path):
"""
Check the saturation of src is higher than tgt and the structures are similar
gimp:554785e9-4523-4e7a-b8e1-8016f565f56a
"""
img_src = Image.open(src_path)
hsv_img_src = img_src.convert('HSV')
img_tgt = Image.open(tgt_path)
hsv_img_tgt = img_tgt.convert('HSV')
# Saturation comparison
src_saturation = measure_saturation(hsv_img_src)
tgt_saturation = measure_saturation(hsv_img_tgt)
saturation_increased = tgt_saturation < src_saturation
# Structure comparison
h1, s1, v1 = hsv_img_src.split()
h2, s2, v2 = hsv_img_tgt.split()
h_same = structure_check_by_ssim(h1, h2)
v_same = structure_check_by_ssim(v1, v2)
if h_same and v_same:
structure_same = True
else:
structure_same = False
return saturation_increased and structure_same
def check_file_exists_and_structure_sim(src_path, tgt_path):
"""
Check if the image has been exported to the desktop
gimp:77b8ab4d-994f-43ac-8930-8ca087d7c4b4
"""
# Check if the file exists
export_file_exists = os.path.isfile(src_path)
if not export_file_exists:
return False
# Check whether the target image is the same as the source image
img_src = Image.open(src_path)
img_tgt = Image.open(tgt_path)
structure_same = structure_check_by_ssim(img_src, img_tgt)
return structure_same
def check_triangle_position(tgt_path):
"""
Check if the triangle is in the middle of the image.
gimp:f4aec372-4fb0-4df5-a52b-79e0e2a5d6ce
"""
# Load the image
img = Image.open(tgt_path)
img_array = np.array(img)
# We will determine if the triangle is in the middle of the picture by checking the centroid
# We assume the triangle is a different color from the background
# Find the unique colors
unique_colors = np.unique(img_array.reshape(-1, img_array.shape[2]), axis=0)
# Assuming the background is the most common color and the triangle is a different color,
# we identify the triangle's color as the least common one
triangle_color = unique_colors[-1]
# Create a mask where the triangle pixels are True
triangle_mask = np.all(img_array == triangle_color, axis=2)
# Get the coordinates of the triangle pixels
triangle_coords = np.argwhere(triangle_mask)
# Calculate the centroid of the triangle
centroid = triangle_coords.mean(axis=0)
# Check if the centroid is approximately in the middle of the image
image_center = np.array(img_array.shape[:2]) / 2
# We will consider the triangle to be in the middle if the centroid is within 5% of the image's center
tolerance = 0.05 * np.array(img_array.shape[:2])
middle = np.all(np.abs(centroid - image_center) < tolerance)
return middle
def check_structure_sim(src_path, tgt_path):
"""
Check if the structure of the two images are similar
gimp:2a729ded-3296-423d-aec4-7dd55ed5fbb3
"""
img_src = Image.open(src_path)
img_tgt = Image.open(tgt_path)
structure_same = structure_check_by_ssim(img_src, img_tgt)
return structure_same
def check_contrast_increase_and_structure_sim(src_path, tgt_path):
"""
Check if the src image has higher contrast than the tgt image and the structures are similar
gimp:f723c744-e62c-4ae6-98d1-750d3cd7d79d
"""
# Load images
source_image = Image.open(src_path)
target_image = Image.open(tgt_path)
# Calculate contrast
source_contrast = calculate_contrast(source_image)
target_contrast = calculate_contrast(target_image)
higher_contrast = target_contrast < source_contrast
# Check structure
structure_same = structure_check_by_ssim(source_image, target_image, threshold=0.65)
return higher_contrast and structure_same
def check_config_status(actual_config_path, rule):
"""
Check if the GIMP status is as expected
"""
with open(actual_config_path, 'r') as f:
content = f.readlines()
for line in content:
if line.startswith('#') or line == '\n':
continue
items = line.strip().lstrip('(').rstrip(')\n').split()
if isinstance(rule["key"], str):
if items[0] == rule["key"] and items[-1] == rule["value"]:
return True
elif isinstance(rule["key"], list) and len(rule["key"]) == 2:
if items[0] == rule["key"][0] \
and items[1] == rule["key"][1] \
and items[-1] == rule["value"]:
return True
return False
def check_image_size_and_structure_sim(src_path, tgt_path, height=512, width=None):
"""
Check if the size of the src image is correct and the structure of the two images are similar.
gimp:d16c99dc-2a1e-46f2-b350-d97c86c85c15
"""
# Load images
source_image = Image.open(src_path)
target_image = Image.open(tgt_path)
# Check size
if width is not None:
width_same = source_image.size[0] == width
else:
width_same = True
if height is not None:
height_same = source_image.size[1] == height
else:
height_same = True
# Check structure
resized_target_image = target_image.resize(source_image.size)
structure_same = structure_check_by_ssim(source_image, resized_target_image)
return width_same and height_same and structure_same
def check_palette_and_structure_sim(src_path, tgt_path):
"""
Check if the src image is palette-based and the structure of the two images are similar
gimp:06ca5602-62ca-47f6-ad4f-da151cde54cc
"""
# Check if the source image is palette-based
source_image = Image.open(src_path)
palette_based = source_image.mode == 'P'
# Check structure
target_image = Image.open(tgt_path)
source_image = source_image.convert('RGB')
structure_same = structure_check_by_ssim(source_image, target_image)
return palette_based and structure_same
def check_textbox_on_leftside(src_path):
"""
Check if the textbox is on the left side of the image.
gimp:e2dd0213-26db-4349-abe5-d5667bfd725c
"""
source_image = Image.open(src_path)
gray_image = source_image.convert("L")
width, height = source_image.size
# Find the bounds of the black text
left_most_dark_pixel = width # Start with the farthest possible left position
for y in range(height):
for x in range(width):
# If the pixel is dark, consider it as part of the text
if gray_image.getpixel((x, y)) < 128: # Arbitrary threshold for "dark"
left_most_dark_pixel = min(left_most_dark_pixel, x)
break # Stop after finding the first dark pixel in this row
# Here we define "almost" on the left side as being within the left 5% of the image
return left_most_dark_pixel < width * 0.05
def check_image_mirror(src_path, tgt_path):
"""
Check if the image is mirrored
gimp:72f83cdc-bf76-4531-9a1b-eb893a13f8aa
"""
# Load images
source_image = Image.open(src_path)
target_image = Image.open(tgt_path)
# Check if the image is mirrored
transposed_image = source_image.transpose(Image.FLIP_LEFT_RIGHT)
# Use 0.99 because the image may not be exactly mirrored by gimp
mirrored = structure_check_by_ssim(transposed_image, target_image, 0.99)
return mirrored
def check_green_background(src_path, tgt_path):
"""
Check if the background of the source image is green.
gimp:734d6579-c07d-47a8-9ae2-13339795476b
"""
# Load images
source_image = Image.open(src_path)
target_image = Image.open(tgt_path)
source_pixels = np.array(source_image)
target_pixels = np.array(target_image)
for x in range(target_image.width):
for y in range(target_image.height):
# Identify background pixel in target image (not black)
if tuple(target_pixels[x, y][:3]) != (0, 0, 0):
# Check if corresponding pixel in source image is green
# Here, "green" means more green than red or blue
r, g, b = source_pixels[x, y][:3]
if not (g > r and g > b):
return False
return True
if __name__ == "__main__":
image1_path = "../Downloads/1.png"
image2_path = "../Downloads/edited_darker.png"
actual_config_path = "../../../cache/sessionrc_test"
rule = {
"key": "hide-docks",
"value": "no"
}
print(check_config_status(actual_config_path, rule))
decrease_brightness(image1_path, image2_path)
actual_config_path = "../../../cache/action-history_test"
rule = {
"key": ["history-item", "\"filters-vignette\""],
"value": "1"
}
print(check_config_status(actual_config_path, rule))
increase_saturation(image1_path, image2_path)
actual_config_path = "../../../cache/gimprc_test"
rule = {
"key": "undo-levels",
"value": "100"
}
print(check_config_status(actual_config_path, rule))
src_path = "../../../cache/734d6579-c07d-47a8-9ae2-13339795476b/green_background_with_object.png"
tgt_path = "../../../cache/734d6579-c07d-47a8-9ae2-13339795476b/white_background_with_object.png"
print(check_green_background(src_path, tgt_path))