Bart/opencv_python_tests
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add separate video loader class

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Bart Moyaers
2019-11-29 10:32:37 +01:00
parent 8ac9d97398
commit c4170aa3b5
4 changed files with 117 additions and 55 deletions
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57
background_subtraction_heat.py
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@@ -6,7 +6,6 @@ from video_loader import VideoLoader
import numpy
from data.library import ArkiteData
from cv2util import to_8_bit_image
from string import digits as DIGITS
class BackgroundHeatmap:
def __init__(self, first_frame, append_blur=True, learning_rate=0.0003):
@@ -54,72 +53,44 @@ class BackgroundHeatmap:
)
)
class RecordingGrouper:
def __init__(self, data: ArkiteData):
self.data = data
def getRecordings(self):
for detection in data.detections(self.data.use_cases()):
for recording in detection.recordings():
yield recording
def getRecordingGroups(self):
groups = []
for recording in self.getRecordings():
# Check if last char is digit
name = recording.name
if name[-1] in DIGITS:
# Remove last two chars:
splitname = name[:-2]
group = next((x for x in groups if x[0] == splitname), None)
if group is not None:
group[1].append(recording)
else:
groups.append((splitname, [recording]))
return groups
if __name__ == '__main__':
projects_path = "C:\\UntrackedGit\\opencv_test\\him_projects"
data = ArkiteData(projects_path, 1)
grouper = RecordingGrouper(data)
groups = grouper.getRecordingGroups()
out = cv2.VideoWriter('outpy.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 30, (512, 424), isColor=False)
loader = VideoLoader(projects_path)
groups = loader.get_recordings_grouped()
# out = cv2.VideoWriter('outpy.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 30, (512, 424), isColor=False)
for group in groups:
heatmaps = []
for recording in group[1]:
print("New recording: " + str(recording.name))
with recording.ir() as ir:
first = True
for frame in ir.frame_sequence():
for frame in VideoLoader.extract_frames(recording):
if first:
heatmap = BackgroundHeatmap(frame)
# Call an update on first frame again like HIM source
heatmap.update(frame)
first = False
converted = to_8_bit_image(frame, display_min=100, display_max=8000)
heatmap.update(converted)
cv2.imshow("IR", converted)
heatmap.update(frame)
cv2.imshow("IR", frame)
# out.write(converted)
cv2.imshow("Heatmap", heatmap.heatmap)
cv2.moveWindow("Heatmap", 600, 100)
# cv2.imshow("Heatmap", heatmap.heatmap)
cv2.imshow("Background filter", heatmap.lastframe)
cv2.moveWindow("Background filter", 600, 100)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# print("Showing frame...")
# time.sleep(0.1)
heatmaps.append(heatmap.heatmap)
cv2.destroyAllWindows()
for i, heatmap in enumerate(heatmaps):
imname = "Heatmap " + str(i)
cv2.imshow(imname, heatmap)
cv2.moveWindow(imname, 500 * i, 0)
cv2.waitKey()
cv2.waitKey(2000)
cv2.destroyAllWindows()
# out.release()
cv2.destroyAllWindows()
# cv2.destroyAllWindows()

27
recording_grouper.py Normal file
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@@ -0,0 +1,27 @@
from data.library import ArkiteData
from string import digits as DIGITS
class RecordingGrouper:
def __init__(self, data: ArkiteData):
self.data = data
def getRecordings(self):
for detection in self.data.detections(self.data.use_cases()):
for recording in detection.recordings():
yield recording
def getRecordingGroups(self):
groups = []
for recording in self.getRecordings():
# Check if last char is digit
name = recording.name
if name[-1] in DIGITS:
# Remove last two chars:
splitname = name[:-2]
group = next((x for x in groups if x[0] == splitname), None)
if group is not None:
group[1].append(recording)
else:
groups.append((splitname, [recording]))
return groups

52
video_loader.py Normal file
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@@ -0,0 +1,52 @@
from enum import Enum
from data.library import ArkiteData, ArkiteDetection, ArkiteRecording
from cv2util import to_8_bit_image
from typing import Iterable
import numpy
from recording_grouper import RecordingGrouper
class VideoType(Enum):
IR = 0
DEPTH = 1
class VideoLoader:
def __init__(self, projects_path: str):
self.projects_path = projects_path
# Search folders with depth of 1:
self.data = ArkiteData(self.projects_path, 1)
def get_all_recordings(self) -> Iterable[ArkiteRecording]:
# Loop over projects
for detection in self.data.detections(self.data.use_cases()):
for recording in detection.recordings():
yield recording
def get_recordings_grouped(self):
grouper = RecordingGrouper(self.data)
return grouper.getRecordingGroups()
@staticmethod
def extract_frames(recording: ArkiteRecording, video_type: VideoType = None) -> Iterable[numpy.ndarray]:
if video_type == VideoType.IR or video_type == None:
disp_min = 100
disp_max = 8000
with recording.ir() as ir:
frames = ir.frame_sequence()
for frame in frames:
yield to_8_bit_image(frame, display_min=disp_min, display_max=disp_max)
elif video_type == VideoType.DEPTH:
# TODO: check if these values make sense for depth images.
disp_min = 100
disp_max = 8000
with recording.depth() as depth:
frames = depth.frame_sequence()
for frame in frames:
yield to_8_bit_image(frame, display_min=disp_min, display_max=disp_max)
else:
raise NotImplementedError("VideoType \'{}\' not implemented".format(video_type))
# Yielding in sub method after "with" statement in top method does not work!
# @staticmethod
# def frames_to_8_bit(frame_sequence, disp_min=None, disp_max=None):
# for frame in frame_sequence:
# yield to_8_bit_image(frame, display_min=disp_min, display_max=disp_max)

12
videoloader_test.py Normal file
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@@ -0,0 +1,12 @@
from video_loader import VideoLoader
import cv2
from cv2util import to_8_bit_image
projects_path = "C:\\UntrackedGit\\opencv_test\\him_projects"
loader = VideoLoader(projects_path)
for recording in loader.get_all_recordings():
frames = loader.extract_frames(recording)
for frame in frames:
cv2.imshow("test", frame)
cv2.waitKey(1)