administrator/frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2026-02-05 10:45:21 +03:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

improve contrast based on averages

Browse Source
This commit is contained in:
Blake Blackshear 2023-06-30 07:07:13 -05:00
parent bf7b53968d
commit 589a1e638d
1 changed files with 18 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

23
frigate/motion/improved_motion.py
View File

@ -19,6 +19,7 @@ class ImprovedMotionDetector(MotionDetector):
name="improved", name="improved",
blur_radius=1, blur_radius=1,
interpolation=cv2.INTER_NEAREST, interpolation=cv2.INTER_NEAREST,
contrast_frame_history=50,
): ):
self.name = name self.name = name
self.config = config self.config = config
@ -44,6 +45,9 @@ class ImprovedMotionDetector(MotionDetector):
self.contour_area = contour_area self.contour_area = contour_area
self.blur_radius = blur_radius self.blur_radius = blur_radius
self.interpolation = interpolation self.interpolation = interpolation
self.contrast_values = np.zeros((contrast_frame_history, 2), np.uint8)
self.contrast_values[:, 1:2] = 255
self.contrast_values_index = 0
def detect(self, frame): def detect(self, frame):
motion_boxes = [] motion_boxes = []
@ -70,13 +74,22 @@ class ImprovedMotionDetector(MotionDetector):
# Improve contrast # Improve contrast
if self.improve_contrast.value: if self.improve_contrast.value:
minval = np.percentile(resized_frame, 4) # TODO tracking moving average of min/max to avoid sudden contrast changes
maxval = np.percentile(resized_frame, 96) minval = np.percentile(resized_frame, 4).astype(np.uint8)
# don't adjust if the image is a single color maxval = np.percentile(resized_frame, 96).astype(np.uint8)
# skip contrast calcs if the image is a single color
if minval < maxval: if minval < maxval:
resized_frame = np.clip(resized_frame, minval, maxval) # keep track of the last 50 contrast values
self.contrast_values[self.contrast_values_index] = [minval, maxval]
self.contrast_values_index += 1
if self.contrast_values_index == len(self.contrast_values):
self.contrast_values_index = 0
avg_min, avg_max = np.mean(self.contrast_values, axis=0)
resized_frame = np.clip(resized_frame, avg_min, avg_max)
resized_frame = ( resized_frame = (
((resized_frame - minval) / (maxval - minval)) * 255 ((resized_frame - avg_min) / (avg_max - avg_min)) * 255
).astype(np.uint8) ).astype(np.uint8)
if self.save_images: if self.save_images: