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yolo_annotation_tool.py
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yolo_annotation_tool.py
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import os
import cv2
import subprocess
import threading
import csv
from recognize_objects import recognize_objects
import configparser
parser = configparser.ConfigParser()
parser.read('config.ini')
data_folder = parser['Settings']['data_folder']
annotation_index = parser['Settings']['annotation_index']
label_file = parser['Settings']['label_file']
output_folder = parser['Settings']['output_folder']
data_folder = data_folder
annotation_index = int(annotation_index)
all_labels = []
ob = recognize_objects("./models/yolov3.weights", "./models/yolov3.cfg","./models/coco.names")
colors = [(255, 0, 0), (255, 255, 0), (0, 255, 0), (0, 255, 255), (0, 0, 255), (255, 0, 255),
(255, 100, 0), (255, 255, 100), (0, 255, 100), (50, 255, 255), (50, 0, 255), (255, 50, 255),
(255, 50, 0), (255, 255, 50), (100, 255, 0), (100, 255, 255), (0, 100, 255), (255, 100, 255),
(255, 0, 100), (255, 255, 150), (50, 255, 50), (150, 255, 255), (0, 50, 255), (255, 150, 255)
]
def get_all_images(dir):
list_of_images = []
for x in os.listdir(dir):
if x.endswith(".png") or x.endswith(".jpeg") or x.endswith(".jpg") :
list_of_images.append(str(dir)+str(x))
return list_of_images
def get_one_image(list_of_images, annotation_index):
return cv2.imread(list_of_images[annotation_index])
def show_image(frame):
cv2.imshow("Annotation Tool", frame)
cv2.waitKey(0)
def list_of_labels():
if all_labels == []:
with open(label_file, mode ='r')as file:
# reading the CSV file
csvFile = csv.reader(file)
# displaying the contents of the CSV file
for lines in csvFile:
lines = str(lines)
lines = lines.replace("['", "")
lines = lines.replace("']", "")
all_labels.append(lines)
return all_labels
def get_label():
ind= 1
labels = ""
with open(label_file, mode ='r')as file:
# reading the CSV file
csvFile = csv.reader(file)
# displaying the contents of the CSV file
for lines in csvFile:
lines = str(lines)
lines = lines.replace("['", "")
lines = lines.replace("']", "")
labels = labels + " \"" + str(ind) + "\" \" " + str(lines) + "\""
ind = ind + 1
return(os.popen("zenity --list --height 500 --title=\"Labels\" --column=\"Index\" --column=\"Label\""+labels).read())
def pre_annotate(frame, all_labels):
ob_results = ob.process_frame(frame, all_labels, False)
return ob_results
def convert_list_to_str(lst):
return str(lst).translate(None, '[],\'')
def convert_boxes_to_yolo(yolo_boxes, frame):
yolo_label = []
for name, box in yolo_boxes:
x = box[0][0]
y = box[0][1]
w = box[1][0] - box[0][0]
h = box[1][1] - box[0][1]
print( frame.shape)
xc = float((x + w/2.0) / frame.shape[1])
yc = float((y + h/2.0) / frame.shape[0])
wc = float(w / frame.shape[1])
hc = float(h / frame.shape[0])
yolo_label.append(' '.join([str(all_labels.index(name)), str(xc), str(yc), str(wc), str(hc)]))
return (yolo_label)
def save_annotation(frame, labels):
output_dir = output_folder
cv2.imwrite(output_dir+str(annotation_index)+".jpg", frame)
file=open(output_dir+str(annotation_index)+".txt",'w')
for items in labels:
file.writelines(items+'\n')
file.close()
print("Annotations saved as: ", labels)
parser.set('Settings', 'annotation_index', str(annotation_index))
fp=open('config.ini','w')
parser.write(fp)
fp.close()
is_clicked = 0
last_click = 0
start_point = []
stop_point = []
temp_point = []
mouse_point = [0,0]
current_label = 'person'
def get_mouse_click(event, x, y, flags, param):
global is_clicked, last_click
global start_point, stop_point, temp_point, mouse_point
if event == cv2.EVENT_LBUTTONDOWN:
is_clicked = 1
if is_clicked != last_click:
start_point = [x,y]
last_click = is_clicked
return start_point
if event == cv2.EVENT_LBUTTONUP:
is_clicked = 0
if is_clicked != last_click:
stop_point = [x,y]
last_click = is_clicked
return stop_point
if start_point:
temp_point = [x,y]
mouse_point = [x,y]
def draw_boxes(frame, yolo_boxes, frame_orig):
global is_clicked
global start_point, stop_point, temp_point,mouse_point
global annotation_index
global current_label
cv2.namedWindow(winname = "Image Annotations")
cv2.setMouseCallback("Image Annotations", get_mouse_click)
keep_running = 1
while keep_running != 0:
for name,boxes in yolo_boxes:
cv2.rectangle(frame, (boxes[0][0],boxes[0][1]) , (boxes[1][0],boxes[1][1]), colors[list_of_labels().index(name)], 2)
cv2.putText(frame, str(name), (boxes[0][0],boxes[0][1]-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, colors[list_of_labels().index(name)], 1, cv2.LINE_AA)
frame_temp = frame.copy()
cv2.imshow("Image Annotations", frame)
ch = cv2.waitKey(3)
if mouse_point[0] > 0 and mouse_point[0] < frame_temp.shape[1] and mouse_point[1] > 0 and mouse_point[1] < frame_temp.shape[0]:
cv2.line(frame_temp, (mouse_point[0], 0), (mouse_point[0], frame_temp.shape[0]), (0,255,255), 1)
cv2.line(frame_temp, (0, mouse_point[1]), (frame_temp.shape[1], mouse_point[1]), (0,255,255), 1)
cv2.rectangle(frame, (0,0), (150,15), (0, 0, 0), -1)
cv2.putText(frame_temp, str(current_label), (5,10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 0), 1, cv2.LINE_AA)
cv2.imshow("Image Annotations", frame_temp)
ch = cv2.waitKey(10)
if start_point and temp_point:
# print(start_point, temp_point)
cv2.rectangle(frame_temp, (start_point[0],start_point[1]) , (temp_point[0], temp_point[1]), (255, 0, 0), 2)
cv2.imshow("Image Annotations", frame_temp)
ch = cv2.waitKey(10)
if start_point and stop_point:
# If there is atleast 10 pixels of distance movement
if abs(start_point[0] - stop_point[0]) > 10:
cv2.rectangle(frame, (start_point[0],start_point[1]), (stop_point[0], stop_point[1]), (255, 0, 255), 2)
yolo_boxes.append([current_label, [(start_point[0],start_point[1]),(stop_point[0], stop_point[1])]])
# Reset points for next box
start_point =[]
stop_point =[]
temp_point = []
if ch == ord('s'):
print("Saved")
annotation_index = annotation_index+1
yolo_labels = convert_boxes_to_yolo(yolo_boxes, frame)
save_annotation(frame_orig, yolo_labels)
print(yolo_labels)
break
elif ch == ord('r'):
print("Reset")
break
elif ch == ord('p'):
print("Previous Frame")
# if annotation_index > 0:
# annotation_index = annotation_index-1
break
elif ch == ord('x'):
print("Skip Frame")
if annotation_index > 0:
annotation_index = annotation_index+1
break
elif ch == ord('l'):
all_labels = list_of_labels()
current_label = all_labels[int(get_label())-1]
print("Label: ", current_label)
elif ch == 27: # ESC to exit
keep_running = 0
print("Exit")
exit()
cv2.destroyAllWindows()
# Code starts from here
list_of_images = get_all_images(data_folder)
for im in range(len(list_of_images)):
frame = get_one_image(list_of_images, annotation_index)
frame_orig = frame.copy()
scale_percent = 70.0
width = int(frame.shape[1] * scale_percent / 100)
height = int(frame.shape[0] * scale_percent / 100)
# dsize
dsize = (width, height)
# resize image
frame = cv2.resize(frame, dsize)
yolo_boxes = pre_annotate(frame,['person', 'car', 'cat', 'dog', 'cow', 'traffic light'])#list_of_labels())
# show_image(frame)
draw_boxes(frame, yolo_boxes, frame_orig)