Spaces:
Build error
Build error
File size: 5,592 Bytes
c914404 |
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 |
import numpy as np
import cv2
# Segmented Absolute Difference (SAD)
# Compares two frames, highlights differences in segments, and returns rectangles of changed areas
def HighlightDifferences(BaseFrame: np.ndarray, NextFrame: np.ndarray, Columns: int = 20, Rows: int = 12, Threshold: float = 10, Padding: int = 1):
FrameHeight, FrameWidth = BaseFrame.shape[:2]
SegmentWidth = FrameWidth // Columns
SegmentHeight = FrameHeight // Rows
HighlightedFrame = BaseFrame.copy()
TotalSegments = 0
SimilarSegments = 0
DifferentSegments = 0
DifferentSegmentMask = np.zeros((Rows, Columns), dtype=bool)
for Row in range(Rows):
for Col in range(Columns):
Y = Row * SegmentHeight
X = Col * SegmentWidth
Y2 = FrameHeight if Row == Rows - 1 else Y + SegmentHeight
X2 = FrameWidth if Col == Columns - 1 else X + SegmentWidth
TotalSegments += 1
SegmentBase = BaseFrame[Y:Y2, X:X2]
SegmentNext = NextFrame[Y:Y2, X:X2]
GreyBase = cv2.cvtColor(SegmentBase, cv2.COLOR_BGR2GRAY)
GreyNext = cv2.cvtColor(SegmentNext, cv2.COLOR_BGR2GRAY)
BlurredBase = cv2.GaussianBlur(GreyBase, (5, 5), 0)
BlurredNext = cv2.GaussianBlur(GreyNext, (5, 5), 0)
AbsDiff = cv2.absdiff(BlurredBase, BlurredNext)
MeanDiff = np.mean(AbsDiff) # type: ignore
if MeanDiff > Threshold:
DifferentSegments += 1
DifferentSegmentMask[Row, Col] = True
else:
SimilarSegments += 1
PaddedMask = DifferentSegmentMask.copy()
for Row in range(Rows):
for Col in range(Columns):
if DifferentSegmentMask[Row, Col]:
for PR in range(max(0, Row - Padding), min(Rows, Row + Padding + 1)):
for PC in range(max(0, Col - Padding), min(Columns, Col + Padding + 1)):
PaddedMask[PR, PC] = True
for Row in range(Rows):
for Col in range(Columns):
Y = Row * SegmentHeight
X = Col * SegmentWidth
Y2 = FrameHeight if Row == Rows - 1 else Y + SegmentHeight
X2 = FrameWidth if Col == Columns - 1 else X + SegmentWidth
SegmentBase = BaseFrame[Y:Y2, X:X2]
if PaddedMask[Row, Col]:
HighlightedFrame[Y:Y2, X:X2] = cv2.addWeighted(
HighlightedFrame[Y:Y2, X:X2], 0.5,
np.full_like(SegmentBase, (0, 0, 255)), 0.2, 0
)
else:
HighlightedFrame[Y:Y2, X:X2] = cv2.addWeighted(
HighlightedFrame[Y:Y2, X:X2], 0.5,
np.full_like(SegmentBase, (0, 255, 0)), 0.2, 0
)
SimilarityPercentage = (SimilarSegments / TotalSegments) * 100
TileCoords = []
for Row in range(Rows):
for Col in range(Columns):
if PaddedMask[Row, Col]:
TileCoords.append((Col, Row))
return HighlightedFrame, DifferentSegments, SimilarityPercentage, TileCoords
def GetRectanglesFromTiles(TileMask: np.ndarray, MinDifferentRatio: float = 0.8):
Height, Width = TileMask.shape
Visited = np.zeros_like(TileMask, dtype=bool)
Rectangles = []
for Y in range(Height):
for X in range(Width):
if TileMask[Y, X] and not Visited[Y, X]:
W = 1
H = 1
Expand = True
while Expand:
Expand = False
if X + W < Width:
NewCol = TileMask[Y:Y+H, X+W] & ~Visited[Y:Y+H, X+W]
if np.any(NewCol):
NewRect = TileMask[Y:Y+H, X:X+W+1] & ~Visited[Y:Y+H, X:X+W+1]
Total = NewRect.size
Diff = np.count_nonzero(NewRect)
Ratio = Diff / Total
if Ratio >= MinDifferentRatio and not np.any(Visited[Y:Y+H, X+W]):
W += 1
Expand = True
if Y + H < Height:
NewRow = TileMask[Y+H, X:X+W] & ~Visited[Y+H, X:X+W]
if np.any(NewRow):
NewRect = TileMask[Y:Y+H+1, X:X+W] & ~Visited[Y:Y+H+1, X:X+W]
Total = NewRect.size
Diff = np.count_nonzero(NewRect)
Ratio = Diff / Total
if Ratio >= MinDifferentRatio and not np.any(Visited[Y+H, X:X+W]):
H += 1
Expand = True
Visited[Y:Y+H, X:X+W] = True
Rectangles.append((X, Y, W, H))
return Rectangles
def GetDifferenceRectangles(BaseFrame, NextFrame, Columns=20, Rows=12, Threshold=5, Padding=1):
HighlightedFrame, DifferentSegments, SimilarPercentage, TileCoords = HighlightDifferences(
BaseFrame, NextFrame, Columns=Columns, Rows=Rows, Threshold=Threshold, Padding=Padding
)
TileMask = np.zeros((Rows, Columns), dtype=bool)
for Col, Row in TileCoords:
if Row < TileMask.shape[0] and Col < TileMask.shape[1]:
TileMask[Row, Col] = True
Rectangles = GetRectanglesFromTiles(TileMask, MinDifferentRatio=0.7)
return {
'HighlightedFrame': HighlightedFrame,
'Rectangles': Rectangles,
'SimilarPercentage': SimilarPercentage,
'TileCoords': TileCoords,
'Columns': Columns,
'Rows': Rows
} |