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dgtlmoon
2025-12-17 16:52:05 +01:00
parent 3b51d03be5
commit fbb019ddf3
13 changed files with 707 additions and 43 deletions
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96
changedetectionio/processors/image_ssim_diff/processor.py
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@@ -14,10 +14,10 @@ from changedetectionio.processors import difference_detection_processor, SCREENS
from changedetectionio.processors.exceptions import ProcessorException
from . import DEFAULT_COMPARISON_METHOD, DEFAULT_COMPARISON_THRESHOLD_OPENCV, DEFAULT_COMPARISON_THRESHOLD_PIXELMATCH
name = 'Visual/Screenshot change detection (Fast)'
name = 'Visual/Image screenshot change detection'
description = 'Compares screenshots using fast algorithms (OpenCV or pixelmatch), 10-100x faster than SSIM'
processor_weight = 2
list_badge_text = "Visual"
class perform_site_check(difference_detection_processor):
"""Fast screenshot comparison processor."""
@@ -84,43 +84,73 @@ class perform_site_check(difference_detection_processor):
url=watch.get('url')
)
# Check if visual selector (include_filters) is set for region-based comparison
include_filters = watch.get('include_filters', [])
# Check if bounding box is set (for drawn area mode)
# Read from processor-specific config JSON file (named after processor)
crop_region = None
# Automatically use the processor name from watch config as filename
processor_name = watch.get('processor', 'default')
config_filename = f'{processor_name}.json'
processor_config = self.get_extra_watch_config(config_filename)
bounding_box = processor_config.get('bounding_box') if processor_config else None
if include_filters and len(include_filters) > 0:
# Get the first filter to use for cropping
first_filter = include_filters[0].strip()
if bounding_box:
try:
# Parse bounding box: "x,y,width,height"
parts = [int(p.strip()) for p in bounding_box.split(',')]
if len(parts) == 4:
x, y, width, height = parts
if first_filter and self.xpath_data:
try:
import json
# xpath_data is JSON string from browser
xpath_data_obj = json.loads(self.xpath_data) if isinstance(self.xpath_data, str) else self.xpath_data
# PIL crop uses (left, top, right, bottom)
crop_region = (
max(0, x),
max(0, y),
min(current_img.width, x + width),
min(current_img.height, y + height)
)
# Find the bounding box for the first filter
for element in xpath_data_obj.get('size_pos', []):
# Match the filter with the element's xpath
if element.get('xpath') == first_filter and element.get('highlight_as_custom_filter'):
# Found the element - extract crop coordinates
left = element.get('left', 0)
top = element.get('top', 0)
width = element.get('width', 0)
height = element.get('height', 0)
logger.info(f"Bounding box enabled: cropping to region {crop_region} (x={x}, y={y}, w={width}, h={height})")
else:
logger.warning(f"Invalid bounding box format: {bounding_box} (expected 4 values)")
except Exception as e:
logger.warning(f"Failed to parse bounding box '{bounding_box}': {e}")
# PIL crop uses (left, top, right, bottom)
crop_region = (
max(0, left),
max(0, top),
min(current_img.width, left + width),
min(current_img.height, top + height)
)
# If no bounding box, check if visual selector (include_filters) is set for region-based comparison
if not crop_region:
include_filters = watch.get('include_filters', [])
logger.info(f"Visual selector enabled: cropping to region {crop_region} for filter: {first_filter}")
break
if include_filters and len(include_filters) > 0:
# Get the first filter to use for cropping
first_filter = include_filters[0].strip()
except Exception as e:
logger.warning(f"Failed to parse xpath_data for visual selector: {e}")
if first_filter and self.xpath_data:
try:
import json
# xpath_data is JSON string from browser
xpath_data_obj = json.loads(self.xpath_data) if isinstance(self.xpath_data, str) else self.xpath_data
# Find the bounding box for the first filter
for element in xpath_data_obj.get('size_pos', []):
# Match the filter with the element's xpath
if element.get('xpath') == first_filter and element.get('highlight_as_custom_filter'):
# Found the element - extract crop coordinates
left = element.get('left', 0)
top = element.get('top', 0)
width = element.get('width', 0)
height = element.get('height', 0)
# PIL crop uses (left, top, right, bottom)
crop_region = (
max(0, left),
max(0, top),
min(current_img.width, left + width),
min(current_img.height, top + height)
)
logger.info(f"Visual selector enabled: cropping to region {crop_region} for filter: {first_filter}")
break
except Exception as e:
logger.warning(f"Failed to parse xpath_data for visual selector: {e}")
# Crop the current image if region was found
if crop_region:
@@ -130,7 +160,7 @@ class perform_site_check(difference_detection_processor):
# Update self.screenshot to the cropped version for history storage
crop_buffer = io.BytesIO()
current_img.save(crop_buffer, format='PNG')
self.screenshot = crop_buffer.getvalue()
self.screenshot = self.fetcher.screenshot = crop_buffer.getvalue()
logger.debug(f"Cropped screenshot to {current_img.size} (region: {crop_region})")
except Exception as e: