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utils.py
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utils.py
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import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
from skimage import draw
def create_folders(folder_paths):
'''
Creates folders
Parameters
----------
folder_paths:
list of folder paths
Output
------
none
'''
for folder in folder_paths:
if not os.path.isdir(folder):
os.makedirs(folder)
return None
def annotate_image(image, bounding_boxes, object_labeles, id_values, colorBGR=(0,255,0)):
'''
Place annotation labels on image
Parameters
----------
image:
image to be annotated
bounding_boxes:
list of rectangle points [x1,y1,x2,y2]
object_labels:
list of object class names, e.g. person, plant, bench...
id_values:
list of object ids used for tracking
colorBGR:
color to use for annotations
Output
------
image:
annotated image
'''
for i, pid in enumerate(id_values):
cv2.rectangle(image,
(bounding_boxes[i][0],bounding_boxes[i][1]),
(bounding_boxes[i][2],bounding_boxes[i][3]),
colorBGR, 2)
cv2.putText(image, object_labeles[i],
(bounding_boxes[i][0]+5, bounding_boxes[i][1]-10),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, colorBGR, 2)
cv2.putText(image, str(int(pid)),
(bounding_boxes[i][0]+5, bounding_boxes[i][3]-10),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, colorBGR, 2)
return image
def get_frames(input_file, save_dir, first_N=None, resize=1.0):
'''
Extracts the frames from an input video file
and saves them as separate frames in an output directory
Parameters
----------
input_file:
input video file
save_dir:
output directory
first_N:
read only the first N frames
resize:
scale frames by interpolating [0, 1]
Output
------
frame_count:
number of frames in video
'''
video = cv2.VideoCapture()
video.open(input_file)
if not video.isOpened():
print("Failed to open input video")
video.release()
return
if first_N:
frame_count = first_N
else:
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_idx = 0
while frame_idx < frame_count:
ret, frame = video.read()
if not ret:
print ("Failed to get the frame {frame_idx:d}")
continue
# resize frame (if required) and save
newdim = (int(frame.shape[1]*resize), int(frame.shape[0]*resize))
frame = cv2.resize(frame, newdim, cv2.INTER_AREA)
out_name = os.path.join(save_dir, f'f{(frame_idx+1):06d}.jpg')
ret = cv2.imwrite(out_name, frame)
if not ret:
print(f"Failed to write the frame {frame_idx:d}")
continue
frame_idx += 1
video.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
return int(frame_count)
def animate_frames(input_path, save_dir, fps=25.0):
'''
Extracts the frames from an input video file
and saves them as separate frames in an output directory.
Parameters
----------
input_path:
input video file
save_dir:
output directory
fps:
frames per second (default: 25)
Output
------
none
'''
dir_frames = input_path
files_info = os.scandir(dir_frames)
file_names = [f.path for f in files_info if f.name.endswith(".jpg")]
file_names.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
frame_Height, frame_Width = cv2.imread(file_names[0]).shape[:2]
resolution = (frame_Width, frame_Height)
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')
video_writer = cv2.VideoWriter(save_dir, fourcc, fps, resolution)
frame_count = len(file_names)
frame_idx = 0
while frame_idx < frame_count:
frame_i = cv2.imread(file_names[frame_idx])
video_writer.write(frame_i)
frame_idx += 1
video_writer.release()
return None
def set_counter_line(img):
'''
Defines the counter line based on the line drawn by user
Parameters
----------
img:
image to draw the counter line on
Output
------
clicked:
coordinates of clicked points
line_coef:
coefficients of counter line equation (a x + b y + c)
'''
print("If it doesn't get you to the drawing mode, then rerun this function again.")
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB).astype('double') / 255.0
fig = plt.figure()
fig.set_label('Draw line to set the counter')
plt.axis('on')
plt.imshow(img, cmap='gray')
xs = []
ys = []
xf = []
yf = []
line_coef = []
clicked = []
def on_mouse_pressed(event):
if len(xs) < 2:
x = event.xdata
y = event.ydata
xs.append(x)
ys.append(y)
plt.plot(x, y, 'ro')
# extend the input points to hit the image borders
if len(xs) == 2:
x1, x2 = xs
y1, y2 = ys
H, W, C = img.shape
x0, xH = None, None
y0, yW = None, None
# line equation
# aa*x + bb*y + c = 0
aa = y1 - y2
bb = x2 - x1
cc = (x1 - x2) * y1 + (y2 - y1) * x1
line_coef = [aa, bb, cc]
# x=0 line
# x=W line
y0 = (-cc - aa * 0) / bb
yW = (-cc - aa * W) / bb
if (y0 < 0) or (y0 >= H):
y0 = None
if (yW < 0) or (yW >= H):
yW = None
# y=0 line
# y=H line
x0 = (-cc - bb * 0) / aa
xH = (-cc - bb * H) / aa
if (x0 < 0) or (x0 >= W):
x0 = None
if (xH < 0) or (xH >= W):
xH = None
if not x0 == None:
xf.append(x0)
yf.append(0)
if not xH == None:
xf.append(xH)
yf.append(H-1)
if not y0 == None:
xf.append(0)
yf.append(y0)
if not yW == None:
xf.append(W-1)
yf.append(yW)
plt.plot(xf, yf, '-', color=(1,1,0))
plt.text(sum(xf)/len(xf), sum(yf)/len(yf), "Counter", size=6,
ha="center", va="center",
bbox=dict(boxstyle="round", ec=(1, 1, 0), fc=(1, 1, 0)))
# Create an hard reference to the callback not to be cleared by the garbage collector
fig.canvas.mpl_connect('button_press_event', on_mouse_pressed)
clicked.append(xf)
clicked.append(yf)
return clicked, line_coef
def find_region(bounding_box, counter_line_coords):
'''
Finds on which side of the counter line the object centroid is
Parameters
----------
bounding_box:
coordinates of the bounding box rectangle [top, left, bottom, right]
counter_line_coords:
coordinates of two points defining the counter line [[x1, x2], [y1, y2]]
Output
------
region:
which side of the counter line the object centroid is
'''
# get coordinates of counter line
x1, x2 = counter_line_coords[0]
y1, y2 = counter_line_coords[1]
# calculate centroid of bounding box
xc = (bounding_box[0] + bounding_box[2]) / 2
yc = (bounding_box[1] + bounding_box[3]) / 2
# decide on what side the object is
v1 = (x2-x1, y2-y1) # vector 1
v2 = (x2-xc, y2-yc) # vector 2
xp = v1[0] * v2[1] - v1[1] * v2[0] # cross product
if xp > 0:
# region A
region = 1
else:
# region B
region = 2
return int(region)
def annotate_counting(image, counted_objects, counter_line_coords,
counter_line_coefs, colorBGR=(0,255,0)):
'''
Place annotation labels for counting the moving objects
Parameters
----------
image:
image to be annotated
counted_objects:
[frame id, object id, rectangle points [x1,y1,x2,y2], regions, countA, countB]
counter_line_coords:
coordinates of two points defining the counter line [[x1, x2], [y1, y2]]
counter_line_coefs:
coefficients [a,b,c] defining the counter line (ax + by + c = 0)
colorBGR:
color to use for annotations
Output
------
image:
annotated image
'''
# draw counter line
counter_color = (0,255,255)
cv2.line(image,
(int(counter_line_coords[0][0]), int(counter_line_coords[1][0])),
(int(counter_line_coords[0][1]), int(counter_line_coords[1][1])),
counter_color, 3)
# draw counter label
xc = int((counter_line_coords[0][0] + counter_line_coords[0][1]) / 2)
yc = int((counter_line_coords[1][0] + counter_line_coords[1][1]) / 2)
label_size = cv2.getTextSize('Counter', cv2.FONT_HERSHEY_SIMPLEX, 0.7, 2)
w = int(label_size[0][0])
h = int(label_size[0][1])
xl = xc - int(w / 2)
yl = yc + int(h / 2)
cv2.rectangle(image, (xl-10, yl-h-5), (xl+w+10, yl+5), counter_color, -1)
cv2.putText(image, 'Counter', (xl, yl), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,0), 2)
# draw region labels on four sides
H, W, C = image.shape
label_size = cv2.getTextSize('B', cv2.FONT_HERSHEY_SIMPLEX, 2, 3)
w = int(label_size[0][0])
h = int(label_size[0][1])
topleft = 'A' if find_region([0, 0, 10, 10], counter_line_coords) == 1 else 'B'
bottomleft = 'A' if find_region([0, H-10, 10, H-1], counter_line_coords) == 1 else 'B'
topright = 'A' if find_region([W-10, 0, W-1, 10], counter_line_coords) == 1 else 'B'
bottomright = 'A' if find_region([W-10, H-10, W-1, H-1], counter_line_coords) == 1 else 'B'
cv2.putText(image, str(topleft), (0, 0+h), cv2.FONT_HERSHEY_SIMPLEX, 2, counter_color, 3)
cv2.putText(image, str(bottomleft), (0, H-1), cv2.FONT_HERSHEY_SIMPLEX, 2, counter_color, 3)
cv2.putText(image, str(topright), (W-1-w, 0+h), cv2.FONT_HERSHEY_SIMPLEX, 2, counter_color, 3)
cv2.putText(image, str(bottomright), (W-1-w, H-1), cv2.FONT_HERSHEY_SIMPLEX, 2, counter_color, 3)
# draw counting related info
for i, obj in enumerate(counted_objects):
bbox = obj[2:6]
region = 'A' if obj[6] == 1 else 'B'
countA = obj[7]
countB = obj[8]
cv2.rectangle(image, (bbox[0],bbox[1]), (bbox[2],bbox[3]), colorBGR, 2)
cv2.putText(image, region, (bbox[0]+10, bbox[1]+30),
cv2.FONT_HERSHEY_SIMPLEX, 1.0, colorBGR, 3)
label_size = cv2.getTextSize('From A to B', cv2.FONT_HERSHEY_SIMPLEX, 1.5, 3)
w = int(label_size[0][0])
h = int(label_size[0][1])
cv2.putText(image, 'From A to B: ' + str(countB), (int(W/2-w/2), H-60),
cv2.FONT_HERSHEY_SIMPLEX, 1.5, counter_color, 3)
cv2.putText(image, 'From B to A: ' + str(countA), (int(W/2-w/2), H-10),
cv2.FONT_HERSHEY_SIMPLEX, 1.5, counter_color, 3)
return image