def pre_process_images(list_folders_scores, recalculate):
print('Start pre_processing images')
# Loading instances
instance_pose = ClassOpenPose()
for folder, min_score in list_folders_scores:
for file in os.listdir(folder):
full_path = os.path.join(folder, file)
extension = ClassUtils.get_filename_extension(full_path)
if extension != '.jpg':
print('Ignoring file {0}'.format(full_path))
continue
file_no_ext = ClassUtils.get_filename_no_extension(full_path)
arr_file_name = os.path.join(folder, '{0}.json'.format(file_no_ext))
# If image recalculation
if not recalculate:
if os.path.isfile(arr_file_name):
print('File already processed {0}'.format(full_path))
continue
# Processing file
print('Processing file {0}'.format(full_path))
image = cv2.imread(full_path)
arr, img_draw = instance_pose.recognize_image_tuple(image)
arr_pass = list()
# Checking vector integrity for all elements
# Verify there is at least one arm and one leg
for elem in arr:
if ClassUtils.check_vector_integrity_part(elem, min_score):
arr_pass.append(elem)
# If there is more than one person with vector integrity
if len(arr_pass) != 1:
for elem in arr_pass:
pt1, pt2 = ClassUtils.get_rectangle_bounds(elem, ClassUtils.MIN_POSE_SCORE)
cv2.rectangle(img_draw, pt1, pt2, (0, 0, 255), 3)
cv2.namedWindow('main_window')
cv2.imshow('main_window', img_draw)
print(arr)
print(arr_pass)
cv2.waitKey(0)
cv2.destroyAllWindows()
raise Exception('Invalid len: {0} file {1}'.format(len(arr_pass), full_path))
person_arr = arr_pass[0]
arr_str = json.dumps(person_arr.tolist())
with open(arr_file_name, 'w') as text_file:
text_file.write(arr_str)
print('Done!')
def test_color_compare():
print('Test color comparision')
print('Loading image comparision')
# Loading instances
instance_pose = ClassOpenPose()
# Avoid to open two prompts
obj_img = ClassDescriptors.load_images_comparision_ext(instance_pose,
min_score,
load_one_img=True)
hist_pose1 = obj_img['listPoints1']
list_process = list()
# Iterating in examples folder
for root, _, files in os.walk(EXAMPLES_FOLDER):
for file in files:
full_path = os.path.join(root, file)
extension = ClassUtils.get_filename_extension(full_path)
if extension == '.jpg':
list_process.append(full_path)
# Sorting list
list_process.sort()
list_result = list()
score_max_pt = -1
for full_path in list_process:
print('Processing file: {0}'.format(full_path))
json_path = full_path.replace('.jpg', '.json')
with open(json_path, 'r') as f:
obj_json = json.loads(f.read())
his_pose2 = obj_json['histPose']
diff = ClassDescriptors.get_kmeans_diff(hist_pose1, his_pose2)
print('Diff {0}'.format(diff))
if diff <= 15:
res = True
else:
res = False
list_result.append({
'filename':
ClassUtils.get_filename_no_extension(full_path),
'score':
res
})
# list_result.sort(key=lambda x: x['score'])
print('Printing list result')
print(json.dumps(list_result, indent=2))
print('min_score: {0}'.format(score_max_pt))
print('Done!')
def reprocess_images(list_folder_data):
print('Init reprocess_images')
for index, item in enumerate(list_folder_data):
folder = item[0]
min_score = item[1]
print('Processing folder: {0}'.format(folder))
list_files = os.listdir(folder)
random.Random(seed).shuffle(list_files)
for num_file, filename in enumerate(list_files):
file = os.path.join(folder, filename)
extension = ClassUtils.get_filename_extension(file)
if extension == '.json':
with open(file, 'r') as f:
data_str = f.read()
data_json = json.loads(data_str)
if 'vectors' in data_json:
print('Processing json file with new format: {0}'.format(file))
person_arr = data_json['vectors']
else:
print('Processing json file: {0}'.format(file))
person_arr = data_json
valid = ClassUtils.check_vector_integrity_pos(person_arr, min_score)
only_pos = ClassUtils.check_vector_only_pos(person_arr, min_score)
if not valid:
raise Exception('Vector integrity not valid for file: {0}'.format(file))
if only_pos:
raise Exception('Invalid vector to perform detection')
descriptors = ClassDescriptors.get_person_descriptors(person_arr, min_score, cam_number=0,
image=None, calib_params=None,
decode_img=False,
instance_nn_pose=None)
with open(file, 'w') as f:
f.write(json.dumps(descriptors))
transformed_points = descriptors['transformedPoints']
# Save pose for debugging purposes
re_scale_factor = 100
new_points = ClassDescriptors.re_scale_pose_factor(transformed_points,
re_scale_factor, min_score)
img_pose = ClassDescriptors.draw_pose_image(new_points, min_score, is_transformed=True)
new_file_name = ClassUtils.get_filename_no_extension(file) + '_1.jpg'
cv2.imwrite(new_file_name, img_pose)
print('Done!')
def cnn_image_generation_folder():
# Initializing instance nn
list_folders = list()
list_folders.append(ClassUtils.cnn_class_folder)
instance_nn = ClassNN(ClassNN.model_dir_pose, classes_number, hidden_layers)
# File walk
for folder in list_folders:
for root, _, files in os.walk(folder):
for file in files:
full_path = os.path.join(root, file)
extension = ClassUtils.get_filename_extension(full_path)
if extension == '.json':
print('Processing: {0}'.format(full_path))
if 'ori' in full_path:
raise Exception('Full path contains ori folder!')
with open(full_path, 'r') as f:
json_txt = f.read()
json_data = json.loads(json_txt)
# All image generation
image_name_pos = ClassUtils.get_filename_no_extension(full_path) + '_p.bmp'
image_name_angle = ClassUtils.get_filename_no_extension(full_path) + '_a.bmp'
image_name_pose = ClassUtils.get_filename_no_extension(full_path) + '_s.bmp'
image_name_angles_black = ClassUtils.get_filename_no_extension(full_path) + '_b.bmp'
image_name_pos_black = ClassUtils.get_filename_no_extension(full_path) + '_o.bmp'
image_name_pos_black_rem = ClassUtils.get_filename_no_extension(full_path) + '_r.bmp'
image_res_pos = create_cnn_image_pos(json_data)
image_res_angle = create_cnn_image_angles(json_data)
image_res_pose = create_cnn_image_pose(json_data, instance_nn)
image_res_angles_black = create_image_cnn_angles_black(json_data)
image_res_pos_black = create_cnn_image_pos_black(json_data)
image_res_pos_black_rem = create_cnn_image_pos_black_rem(json_data)
# print('Writing image pos: {0}'.format(image_name_pos))
cv2.imwrite(image_name_pos, image_res_pos)
# print('Writing image angle: {0}'.format(image_name_angle))
cv2.imwrite(image_name_angle, image_res_angle)
# print('Writing image pose: {0}'.format(image_name_pose))
cv2.imwrite(image_name_pose, image_res_pose)
# print('Writing image angles black: {0}'.format(image_name_angles_black))
cv2.imwrite(image_name_angles_black, image_res_angles_black)
# print('Writing image pos black: {0}'.format(image_name_pos_black))
cv2.imwrite(image_name_pos_black, image_res_pos_black)
print('Writing image pos black rem: {0}'.format(image_name_pos_black_rem))
cv2.imwrite(image_name_pos_black_rem, image_res_pos_black_rem)
print('Done!')
def re_process_folder():
print('Init folder processing')
init_dir = '/home/mauricio/Pictures/BTF'
options = {'initialdir': init_dir}
folder = filedialog.askdirectory(**options)
if folder is None:
raise Exception('Folder not selected!')
files = os.listdir(folder)
for file in files:
full_path = os.path.join(folder, file)
ext = ClassUtils.get_filename_extension(full_path)
if ext == '.jpg':
print('Processing file: {0}'.format(full_path))
file_json = ClassUtils.get_filename_no_extension(
full_path) + '.json'
with open(file_json, 'r') as f:
json_txt = f.read()
json_data = json.loads(json_txt)
if 'vectors' in json_data:
vectors = json_data['vectors']
elif 'vector' in json_data:
vectors = json_data['vector']
else:
raise Exception('Vector not found!')
img_cv = cv2.imread(full_path)
param = ClassDescriptors.get_person_descriptors(vectors,
min_score,
image=img_cv,
decode_img=False)
with open(file_json, 'w') as f:
f.write(json.dumps(param, indent=2))
print('Done!')
def main():
print('Initializing main function')
# Withdrawing TKInter
Tk().withdraw()
# Ask for directory
init_dir = '/home/mauricio/CNN/Images'
options = {'initialdir': init_dir}
dir_name = filedialog.askdirectory(**options)
if not dir_name:
print('Directory not selected')
else:
for root, subdirs, files in os.walk(dir_name):
for file in files:
full_path = os.path.join(root, file)
print('Processing {0}'.format(full_path))
extension = ClassUtils.get_filename_extension(file)
if extension != '.jpg':
print('Ignoring file no jpg {0}'.format(full_path))
continue
name = ClassUtils.get_filename_no_extension(file)
if len(name) < total_digits:
new_name = ''
for _ in range(total_digits - len(name)):
new_name += '0'
new_name += name
new_name += extension
new_full_path = os.path.join(root, new_name)
print('Rename file {0} to {1}'.format(full_path, new_full_path))
os.rename(full_path, new_full_path)
print('Done!')
def main():
print('Initializing main function')
# Initializing instances
instance_pose = ClassOpenPose()
# Withdrawing tkinter
Tk().withdraw()
# Loading folder images
folder_images = '/home/mauricio/PosesProcessed/folder_images'
folder_images_draw = '/home/mauricio/PosesProcessed/folder_images_draw'
pose_base_folder = '/home/mauricio/Pictures/PosesNew'
# Reading all elements in list
list_files = sorted(os.listdir(folder_images_draw))
cv2.namedWindow('main_window', cv2.WND_PROP_AUTOSIZE)
index = 0
while True:
file = list_files[index]
full_path_draw = os.path.join(folder_images_draw, file)
image_draw = cv2.imread(full_path_draw)
cv2.imshow('main_window', image_draw)
key = cv2.waitKey(0)
print('Key pressed: {0}'.format(key))
if key == 52:
# Left arrow
index -= 1
if index < 0:
index = 0
elif key == 54:
# Right arrow
index += 1
if index == len(list_files):
index = len(list_files) - 1
elif key == 27:
# Esc
# Ask are you sure question
result = messagebox.askyesno("Exit", "Are you sure to exit?")
print(result)
if result:
break
elif key == 115:
# Check JSON file
image_full_path = os.path.join(folder_images, file)
json_path = image_full_path.replace(".jpg", ".json")
if not os.path.exists(json_path):
# Generating JSON array
image = cv2.imread(image_full_path)
arr = instance_pose.recognize_image(image).tolist()
else:
with open(json_path, 'r') as file:
arr_str = file.read()
arr = json.load(arr_str)
arr_pass = []
min_score = 0.05
# Drawing candidates
for elem in arr:
if ClassUtils.check_vector_integrity_part(elem, min_score):
arr_pass.append(elem)
if len(arr_pass) == 0:
print('Arr pass size equals to zero')
continue
elif len(arr_pass) == 1:
selection_int = 0
person_arr = arr_pass[0]
arr_str = json.dumps(person_arr)
else:
# Draw rectangles for all candidates
for index_elem, person_arr in enumerate(arr_pass):
pt1, pt2 = ClassUtils.get_rectangle_bounds(person_arr, min_score)
cv2.rectangle(image_draw, pt1, pt2, (0, 0, 255), 5)
font = cv2.FONT_HERSHEY_SIMPLEX
bottom_left_corner = pt2
font_scale = 0.6
font_color = (255, 255, 255)
line_type = 2
cv2.putText(image_draw, '{0}'.format(index_elem),
bottom_left_corner,
font,
font_scale,
font_color,
line_type)
while True:
print('Select image to put')
cv2.imshow('main_window', image_draw)
wait_key = cv2.waitKey(0)
print('Wait Key: {0}'.format(wait_key))
selection_int = ClassUtils.key_to_number(wait_key)
print('Selection: {0}'.format(selection_int))
if 0 <= selection_int < len(arr_pass):
break
person_arr = arr_pass[selection_int]
arr_str = json.dumps(person_arr)
# Getting new image using numpy slicing
pt1, pt2 = ClassUtils.get_rectangle_bounds(person_arr, min_score)
image_draw = image_draw[pt1[1]:pt2[1], pt1[0]:pt2[0]]
# Selecting directory after processing image!
init_dir = '/home/mauricio/Pictures/PosesNew'
options = {'initialdir': init_dir}
dir_name = filedialog.askdirectory(**options)
if not dir_name:
print('Directory not selected')
else:
new_name = ClassUtils.get_filename_no_extension(file)
new_name = "{0}_{1}.{2}".format(new_name, selection_int, 'jpg')
new_image_path = os.path.join(dir_name, new_name)
new_json_path = os.path.join(dir_name, new_name.replace('.jpg', '.json'))
cv2.imwrite(new_image_path, image_draw)
with open(new_json_path, 'w') as file:
file.write(arr_str)
print('File copied from {0} to {1}'.format(full_path_draw, new_image_path))
index += 1
if index == len(list_files):
index = len(list_files) - 1
cv2.destroyAllWindows()
print('Done!')