def find_galabal_matches(pose):
model = galabaljson+pose+".json"
model_features = common.parse_JSON_multi_person(model)
count = 0
os.system("mkdir -p "+galabal+pose)
os.system("mkdir -p "+galabal+pose+"/json")
os.system("mkdir -p "+galabal+pose+"/jsonfout")
os.system("mkdir -p "+galabal+pose+"/fotos")
os.system("mkdir -p "+galabal+pose+"/fotosfout")
for json in glob.iglob(galabaljson+"*.json"):
logger.info(json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, normalise=True)
if result == True:
place = json.split(".json")[0]
place = place.split("json/")[1]
place = place+".json"
os.system("cp "+json+" "+galabal+pose+"/json/"+place)
foto = json.split(".json")[0];
foto = foto.replace("json","fotos")
foto = foto +".jpg"
os.system("cp "+foto+" "+galabal+pose+"/fotos/")
count = count+1
logger.info("true")
print ("there are "+str(count)+" matches found")
def check_matches(pose):
global eucl_dis_tresh_torso
global rotation_tresh_torso
global eucl_dis_tresh_legs
global rotation_tresh_legs
global eucld_dis_shoulders_tresh
eucl_dis_tresh_torso= 0.18
rotation_tresh_torso= 19
eucl_dis_tresh_legs= 0.058
rotation_tresh_legs= 24
eucld_dis_shoulders_tresh= 0.125
path = poses+pose
model = path+"/json/"+pose+".json"
#pose = "1"
#path = '/media/jochen/2FCA69D53AB1BFF41/dataset/poses/pose'+pose
#model = path+"/json/0.json"
model_features = common.parse_JSON_multi_person(model)
true_positive =0
false_positive =0
true_negative =0
false_negative =0
for json in glob.iglob(path+"/json/*.json"):
#print (json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, True)
if result == True:
true_positive = true_positive +1
else:
false_negative = false_negative +1
print ("error at: "+json)
for json in glob.iglob(path+"/jsonfout/*.json"):
#print (json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, True)
if result == True:
false_positive = false_positive +1
print ("error at: "+json)
else:
true_negative = true_negative +1
precision = 0
recall =0
if (true_positive+false_positive) !=0:
precision = true_positive / (true_positive+false_positive)
if (true_positive+false_negative) !=0:
recall = true_positive / (true_positive+false_negative)
#******** print small raport ******************
print ("*************raport of pose "+pose+" ****************")
print ("true_positive: " + str(true_positive))
print ("false_positive: "+ str(false_positive))
print ("true_negative: " + str(true_negative))
print ("false_negative: "+ str(false_negative))
print ("recall: "+ str(recall))
print ("precision: "+ str(precision))
def check_galabal_matches(pose):
model = galabal+pose+"/json/"+pose+".json"
model_features = common.parse_JSON_multi_person(model)
count =0
for json in glob.iglob(galabal+pose+"/json/*.json"):
logger.info(json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, normalise=True)
if result == False:
count = count +1
print ("error at: "+json)
print (str(count)+" foto's werden niet meer herkend")
def calculate_pr(pose):
path = poses+pose
model = path+"/json/"+pose+".json"
#pose = "1"
#path = '/media/jochen/2FCA69D53AB1BFF41/dataset/poses/pose'+pose
#model = path+"/json/0.json"
model_features = common.parse_JSON_multi_person(model)
true_positive =0
false_positive =0
true_negative =0
false_negative =0
for json in glob.iglob(path+"/json/*.json"):
#print (json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, True)
if result == True:
true_positive = true_positive +1
else:
false_negative = false_negative +1
print ("error at: "+json)
for json in glob.iglob(path+"/jsonfout/*.json"):
#print (json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, True)
if result == True:
false_positive = false_positive +1
print ("error at: "+json)
else:
true_negative = true_negative +1
precision = 0
recall =0
if (true_positive+false_positive) !=0:
precision = true_positive / (true_positive+false_positive)
if (true_positive+false_negative) !=0:
recall = true_positive / (true_positive+false_negative)
#******** print small raport ******************
print ("*************raport of pose "+pose+" ****************")
print ("true_positive: " + str(true_positive))
print ("false_positive: "+ str(false_positive))
print ("true_negative: " + str(true_negative))
print ("false_negative: "+ str(false_negative))
print ("recall: "+ str(recall))
print ("precision: "+ str(precision))
return (precision,recall)
def find_matches_with(pose):
global eucl_dis_tresh_torso
global rotation_tresh_torso
global eucl_dis_tresh_legs
global rotation_tresh_legs
global eucld_dis_shoulders_tresh
eucl_dis_tresh_torso= 0.18
rotation_tresh_torso= 19
eucl_dis_tresh_legs= 0.058
rotation_tresh_legs= 24
eucld_dis_shoulders_tresh= 0.125
if len(pose) == 5 and pose.isdigit():
model = data+pose+"_keypoints.json"
model_features = common.parse_JSON_multi_person(model)
count = 0
os.system("mkdir -p "+poses+pose)
os.system("mkdir -p "+poses+pose+"/json")
os.system("mkdir -p "+poses+pose+"/jsonfout")
os.system("mkdir -p "+poses+pose+"/fotos")
os.system("mkdir -p "+poses+pose+"/fotosfout")
for json in glob.iglob(data+"*_keypoints.json"):
logger.info(json)
input_features = common.parse_JSON_multi_person(json)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, normalise=True)
if result == True:
place = json.split("_keypoints")[0]
place = place.split("json/")[1]
place = place+".json"
os.system("cp "+json+" "+poses+pose+"/json/"+place)
foto = json.split("_keypoints")[0];
foto = foto.replace("json","fotos")
foto = foto +".jpg"
os.system("cp "+foto+" "+poses+pose+"/fotos/")
count = count+1
logger.info("true")
print ("there are "+str(count)+" matches found")
else:
print ("find_matches_with has wrong input")
def test_script():
pose = "00100"
model = poses+pose+"/json/"+pose+".json"
model_features = common.parse_JSON_multi_person(model)
input = poses+pose+"/json/01179.json"
global eucl_dis_tresh_torso
global rotation_tresh_torso
global eucl_dis_tresh_legs
global rotation_tresh_legs
global eucld_dis_shoulders_tresh
eucl_dis_tresh_torso= 0.18
rotation_tresh_torso= 19
eucl_dis_tresh_legs= 0.058
rotation_tresh_legs= 24
eucld_dis_shoulders_tresh= 0.125
input_features = common.parse_JSON_multi_person(input)
(result, error_score, input_transform,something) = multiperson.match(model_features, input_features, normalise=True)
print (result)
plot_us = True # plot urban scene
plot_mp = False # plot multi pose
plot_vars.input_name = input_name
plot_vars.model_name = model_name
plot_vars.model_path = path_img + model_name
plot_vars.input_path = path_img + input_name
plot_vars.write_img = False
global crop
global correction
crop = True
correction = True
logger.debug("---Starting pose matching --")
if include_keypoints:
model_pose_features = common.parse_JSON_multi_person(
path_json + model_name.split('.')[0] + '_keypoints' +
'.json') # + '_keypoints'
input_pose_features = common.parse_JSON_multi_person(
path_json + input_name.split('.')[0] + '_keypoints' + '.json')
else:
model_pose_features = common.parse_JSON_multi_person(
path_json + model_name.split('.')[0].replace('fotos', 'json') +
'.json') # + '_keypoints'
input_pose_features = common.parse_JSON_multi_person(
path_json + input_name.split('.')[0].replace('fotos', 'json') +
'.json')
result_whole = matching.match_whole(model_pose_features, input_pose_features,
detector, matcher, model_image,
input_image, plot_us, plot_mp)
diff = np.abs(A - B)
new_distance = dist(A, B)
new_distance = ((diff[0])**2 + diff[1]**2)**0.5
if new_distance > distance:
distance = new_distance
biggest = id
id = id + 1
return biggest
# test_file = path + "testje.json"
# poses = common.parse_JSON_multi_person(test_file)
# filter_poses(poses, test_file)
f = []
for (dirpath, dirnames, filenames) in walk(path):
f.extend(filenames)
break
print(f)
for f_name in f:
poses = common.parse_JSON_multi_person(path + f_name)
lenght = len(poses)
if lenght > 1:
filter_poses(poses, path + f_name)
logger.info('using ' + feature_name )
plot = True
include_keypoints = False
for i in range(start_counter, end_counter+1):
model_image = cv2.imread(path_img + model_name + str(i) + img_type, cv2.IMREAD_GRAYSCALE)
if model_image is None:
logger.info('Failed to load fn1: %s', model_name + str(i) + img_type)
continue
#sys.exit(1)
#model_pose_features = common.parse_JSON_single_person(path_json + model_name + str(i) + '_keypoints' + '.json') # + '_keypoints'
if include_keypoints:
model_pose_features = common.parse_JSON_multi_person(path_json + model_name + str(i) + '_keypoints' + '.json') # + '_keypoints'
else:
model_pose_features = common.parse_JSON_multi_person(
path_json + model_name + str(i) + '.json') # + '_keypoints'
intermediate_result = {}
for j in range(start_counter, end_counter+1):
logger.info("@@@@@@ Matching model(%d) with input(%d) @@@@@@@@@", i, j)
if i == j:
logger.info("--> Skip: don't compare the same image")
continue # don't compare the same image
input_image = cv2.imread(path_img + input_name + str(j) + img_type, cv2.IMREAD_GRAYSCALE)
if input_image is None:
logger.info('Failed to load fn2:', input_name + str(j) + img_type)
json_data_path = '../specials/MP_overlapping/' #'../json_data/'
images_data_path = '../specials/MP_overlapping/' #'../img/'
json_data_path = '../json_data/' #'../json_data/'
images_data_path = '../img/' #'../img/'
#json_data_path = '../json_data/' #'../json_data/'
#images_data_path = '../img/' #'../img/'
'''
-------------------- MULTI PERSON -------------------------------------
'''
model = "3" # "duo3" # "09958" #
input = "kleuter9" #"duo4" # "08425" #
model_json = json_data_path + model + '.json'
input_json = json_data_path + input + '_keypoints.json'
model_image = images_data_path + model + '.png'
input_image = images_data_path + input + '.jpg'
model_features = parse_JSON_multi_person(model_json)
input_features = parse_JSON_multi_person(input_json)
#plot_poses(np.vstack(model_features), np.vstack(input_features), model_image_name=model_image, input_image_name=input_image)
matchresult = match(model_features,
input_features,
normalise=True,
plot=True,
model_image=model_image,
input_image=input_image)
logger.info("Match result: %s", str(matchresult.match_bool))
plt.show()