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Enabling different colours for different objects helping distinguish things in a busy scene

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This commit is contained in:
Luiz Pizzato 2019-09-17 23:05:36 +10:00
parent ba71927d53
commit 2cabb784cd
5 changed files with 19 additions and 11 deletions
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2
Dockerfile
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@ -101,6 +101,8 @@ RUN ln -s /coco_labels.txt /label_map.pbtext
RUN (apt-get autoremove -y; \ RUN (apt-get autoremove -y; \
apt-get autoclean -y) apt-get autoclean -y)
RUN pip install -U matplotlib
WORKDIR /opt/frigate/ WORKDIR /opt/frigate/
ADD frigate frigate/ ADD frigate frigate/
COPY detect_objects.py . COPY detect_objects.py .

1
frigate/object_detection.py
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@ -47,6 +47,7 @@ class PreppedQueueProcessor(threading.Thread):
box = obj.bounding_box.flatten().tolist() box = obj.bounding_box.flatten().tolist()
parsed_objects.append({ parsed_objects.append({
'frame_time': frame['frame_time'], 'frame_time': frame['frame_time'],
'label_id': obj.label_id,
'name': str(self.labels[obj.label_id]), 'name': str(self.labels[obj.label_id]),
'score': float(obj.score), 'score': float(obj.score),
'xmin': int((box[0] * frame['region_size']) + frame['region_x_offset']), 'xmin': int((box[0] * frame['region_size']) + frame['region_x_offset']),

6
frigate/objects.py
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@ -81,8 +81,10 @@ class BestPersonFrame(threading.Thread):
if not self.best_person is None and self.best_person['frame_time'] in recent_frames: if not self.best_person is None and self.best_person['frame_time'] in recent_frames:
best_frame = recent_frames[self.best_person['frame_time']] best_frame = recent_frames[self.best_person['frame_time']]
label = "{}: {}% {}".format(self.best_person['name'],int(self.best_person['score']*100),int(self.best_person['area']))
draw_box_with_label(best_frame, self.best_person['xmin'], self.best_person['ymin'], draw_box_with_label(best_frame, self.best_person['xmin'], self.best_person['ymin'],
self.best_person['xmax'], self.best_person['ymax'], label) self.best_person['xmax'], self.best_person['ymax'],
self.best_person['name'], self.best_person['score'], self.best_person['area'],
(255, 0, 0)
)
self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR) self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)

6
frigate/util.py
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@ -5,11 +5,11 @@ import cv2
def tonumpyarray(mp_arr): def tonumpyarray(mp_arr):
return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8) return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8)
def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label): def draw_box_with_label(frame, x_min, y_min, x_max, y_max, name, score, area, color):
color = (255,0,0) label = "{}: {}% {}".format(name, int(score * 100), int(area))
cv2.rectangle(frame, (x_min, y_min), cv2.rectangle(frame, (x_min, y_min),
(x_max, y_max), (x_max, y_max),
color, 2) color, 1)
font_scale = 0.5 font_scale = 0.5
font = cv2.FONT_HERSHEY_SIMPLEX font = cv2.FONT_HERSHEY_SIMPLEX
# get the width and height of the text box # get the width and height of the text box

7
frigate/video.py
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@ -11,6 +11,7 @@ from . util import tonumpyarray, draw_box_with_label
from . object_detection import FramePrepper from . object_detection import FramePrepper
from . objects import ObjectCleaner, BestPersonFrame from . objects import ObjectCleaner, BestPersonFrame
from . mqtt import MqttObjectPublisher from . mqtt import MqttObjectPublisher
import matplotlib.pyplot as plt
# Stores 2 seconds worth of frames when motion is detected so they can be used for other threads # Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
class FrameTracker(threading.Thread): class FrameTracker(threading.Thread):
@ -207,6 +208,7 @@ class Camera:
self.mask = np.zeros((self.frame_shape[0], self.frame_shape[1], 1), np.uint8) self.mask = np.zeros((self.frame_shape[0], self.frame_shape[1], 1), np.uint8)
self.mask[:] = 255 self.mask[:] = 255
self.color_map = plt.cm.get_cmap('tab20', 100)
def start_or_restart_capture(self): def start_or_restart_capture(self):
if not self.ffmpeg_process is None: if not self.ffmpeg_process is None:
@ -316,8 +318,9 @@ class Camera:
# draw the bounding boxes on the screen # draw the bounding boxes on the screen
for obj in detected_objects: for obj in detected_objects:
label = "{}: {}% {}".format(obj['name'],int(obj['score']*100),int(obj['area'])) color = tuple(int(round(255 * c)) for c in self.color_map(obj['label_id'])[:3])
draw_box_with_label(frame, obj['xmin'], obj['ymin'], obj['xmax'], obj['ymax'], label) draw_box_with_label(frame, obj['xmin'], obj['ymin'], obj['xmax'], obj['ymax'],
obj['name'], obj['score'], obj['area'], color)
for region in self.regions: for region in self.regions:
color = (255,255,255) color = (255,255,255)