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use a regular subprocess for ffmpeg, refactor bounding box drawing

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blakeblackshear
2019-06-02 07:29:50 -05:00
committed by Blake Blackshear
parent 2b51dc3e5b
commit baa587028b
5 changed files with 68 additions and 51 deletions
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2
frigate/object_detection.py
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@@ -89,8 +89,6 @@ class FramePrepper(threading.Thread):
cropped_frame = self.shared_frame[self.region_y_offset:self.region_y_offset+self.region_size, self.region_x_offset:self.region_x_offset+self.region_size].copy()
frame_time = self.frame_time.value
# convert to RGB
#cropped_frame_rgb = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2RGB)
# Resize to 300x300 if needed
if cropped_frame.shape != (300, 300, 3):
cropped_frame = cv2.resize(cropped_frame, dsize=(300, 300), interpolation=cv2.INTER_LINEAR)

12
frigate/objects.py
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@@ -2,6 +2,7 @@ import time
import datetime
import threading
import cv2
from . util import draw_box_with_label
class ObjectCleaner(threading.Thread):
def __init__(self, objects_parsed, detected_objects):
@@ -79,12 +80,9 @@ class BestPersonFrame(threading.Thread):
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 = cv2.cvtColor(best_frame, cv2.COLOR_BGR2RGB)
# draw the bounding box on the frame
color = (255,0,0)
cv2.rectangle(best_frame, (self.best_person['xmin'], self.best_person['ymin']),
(self.best_person['xmax'], self.best_person['ymax']),
color, 2)
# convert back to BGR
label = "{}: {}%".format(self.best_person['name'],int(self.best_person['score']*100))
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_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)

23
frigate/util.py
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@@ -1,5 +1,26 @@
import numpy as np
import cv2
# convert shared memory array into numpy array
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):
color = (255,0,0)
cv2.rectangle(frame, (x_min, y_min),
(x_max, y_max),
color, 2)
font_scale = 0.5
font = cv2.FONT_HERSHEY_SIMPLEX
# get the width and height of the text box
size = cv2.getTextSize(label, font, fontScale=font_scale, thickness=2)
text_width = size[0][0]
text_height = size[0][1]
line_height = text_height + size[1]
# set the text start position
text_offset_x = x_min
text_offset_y = 0 if y_min < line_height else y_min - line_height
# make the coords of the box with a small padding of two pixels
textbox_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y + line_height))
cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
cv2.putText(frame, label, (text_offset_x, text_offset_y + line_height - 2), font, fontScale=font_scale, color=(0, 0, 0), thickness=2)

52
frigate/video.py
View File

@@ -5,9 +5,10 @@ import cv2
import threading
import ctypes
import multiprocessing as mp
import subprocess as sp
import numpy as np
import ffmpeg
from . util import tonumpyarray
from . util import tonumpyarray, draw_box_with_label
from . object_detection import FramePrepper
from . objects import ObjectCleaner, BestPersonFrame
from . mqtt import MqttObjectPublisher
@@ -16,34 +17,29 @@ from . mqtt import MqttObjectPublisher
def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_shape, rtsp_url):
# convert shared memory array into numpy and shape into image array
arr = tonumpyarray(shared_arr).reshape(frame_shape)
frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
ffmpeg_process = (
ffmpeg
.input(rtsp_url,
rtsp_transport="tcp",
stimeout=5000000,
use_wallclock_as_timestamps=1,
fflags="+genpts",
avoid_negative_ts="make_zero")
.output('pipe:', format='rawvideo', pix_fmt='rgb24')
)
print(ffmpeg_process.compile())
ffmpeg_process = ffmpeg_process.run_async(pipe_stdout=True)
ffmpeg_cmd = ['ffmpeg',
'-avoid_negative_ts', 'make_zero',
'-fflags', '+genpts',
'-rtsp_transport', 'tcp',
'-stimeout', '5000000',
'-use_wallclock_as_timestamps', '1',
'-i', rtsp_url,
'-f', 'rawvideo',
'-pix_fmt', 'rgb24',
'pipe:']
pipe = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, bufsize=frame_size)
while True:
in_bytes = ffmpeg_process.stdout.read(frame_shape[0] * frame_shape[1] * frame_shape[2])
if not in_bytes:
print("No bytes received. Waiting 1 second before trying again.")
time.sleep(1)
continue
raw_image = pipe.stdout.read(frame_size)
frame = (
np
.frombuffer(in_bytes, np.uint8)
.frombuffer(raw_image, np.uint8)
.reshape(frame_shape)
)
# Lock access and update frame
with frame_lock:
shared_frame_time.value = datetime.datetime.now().timestamp()
arr[:] = frame
@@ -51,7 +47,7 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
with frame_ready:
frame_ready.notify_all()
ffmpeg_process.wait()
pipe.stdout.flush()
# Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
class FrameTracker(threading.Thread):
@@ -272,14 +268,10 @@ class Camera:
with self.frame_lock:
frame = self.shared_frame_np.copy()
# convert to RGB for drawing
#frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# draw the bounding boxes on the screen
for obj in detected_objects:
color = (255,0,0)
cv2.rectangle(frame, (obj['xmin'], obj['ymin']),
(obj['xmax'], obj['ymax']),
color, 2)
label = "{}: {}%".format(obj['name'],int(obj['score']*100))
draw_box_with_label(frame, obj['xmin'], obj['ymin'], obj['xmax'], obj['ymax'], label)
for region in self.regions:
color = (255,255,255)
@@ -287,7 +279,7 @@ class Camera:
(region['x_offset']+region['size'], region['y_offset']+region['size']),
color, 2)
# convert back to BGR
# convert to BGR
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
return frame