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 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_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_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 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)
def findmatch(filename, id):
os.system(
"./build/examples/openpose/openpose.bin -write_keypoint_json /home/jochen/fotos/json -image_dir /home/jochen/fotos/processing -write_images /home/jochen/fotos/calculated_poses/ -no_display"
)
os.system("mv -v /home/jochen/fotos/processing/* /home/jochen/fotos/poses")
filename = filename.rsplit('.')[0]
inputadr = "/home/jochen/fotos/json/" + filename + '_keypoints.json'
modeladr = "/home/jochen/dataset/poses/pose" + id + "/json/0.json"
#find matched
model_features = parse_JSON_single_person(modeladr)
input_features = parse_JSON_single_person(inputadr)
(result, error_score,
input_transform) = multi_person.match(model_features, input_features,
True)
print("Match or not: ", result)
with open(inputadr) as json_file:
json_decoded = json.load(json_file)
json_decoded['match'] = bool(result)
return jsonify(json_decoded)
return json_data #jsonify(json_data)
def match_whole(model_pose_features,
input_pose_features,
detector,
matcher,
model_image,
input_image,
plot_us=False,
plot_mp=False):
result_pose_matching = multi_person.match(model_pose_features,
input_pose_features,
normalise=True,
plot=plot_mp,
input_image=input_image,
model_image=model_image)
#logger.debug("---Result pose matching: --")
#logger.debug(result_pose_matching)
if result_pose_matching.match_bool:
#logger.debug(result_pose_matching.matching_permutations)
logger.info("===> Pose matching succes!")
else:
logger.info("No matching poses found, so quit URBAN SCENE MATCHING")
if plot_us or plot_mp:
f = plt.figure(figsize=(10, 8))
fs = 10 #fontsize
markersize = 3
f.suptitle("No matching poses found, so quit URBAN SCENE MATCHING",
fontsize=10)
plt.subplot(1, 2, 1)
plt.imshow(np.asarray(input_image), cmap='gray')
for i in range(0, len(input_pose_features)):
plt.plot(*zip(*input_pose_features[i]),
marker='o',
color='blue',
label='pose',
ls='',
ms=markersize - 1)
plt.title("input: " + plot_vars.input_name + " (" +
str(plot_vars.amount_input_persons) + " pers)",
fontsize=fs)
plt.subplot(1, 2, 2)
plt.imshow(np.asarray(model_image), cmap='gray')
for i in range(0, len(model_pose_features)):
plt.plot(*zip(*model_pose_features[i]),
marker='o',
color='blue',
label='pose',
ls='',
ms=markersize - 1)
plt.title("model: " + plot_vars.model_name + " (" +
str(plot_vars.amount_model_persons) + " pers)",
fontsize=fs)
plot_name = plot_vars.model_name.split(
".")[0] + "_" + plot_vars.input_name.split(".")[0] + "_FALSE"
plt.savefig('./plots/' + plot_name + '.png')
return (False, False)
#exit()
logger.debug("--- Starting urbanscene matching ---")
# Loop over all found matching comnbinations
# And order input poses according to matching model poses
for matching_permuations, result in result_pose_matching.matching_permutations.items(
):
model_poses = result['model']
input_poses = result['input']
#logger.debug(model_poses)
#logger.debug(input_poses)
model_image_copy = model_image #TODO make hard copy ??
input_image_copy = input_image
error = match_scene_multi(detector, matcher, model_image_copy,
input_image_copy, model_poses, input_poses,
plot_us)
if error <= thresholds.AFFINE_TRANS_WHOLE_DISTANCE:
logger.info(
"===> MATCH! permutation %s score:%0.4f (thresh ca %0.4f)",
matching_permuations, round(error, 4),
thresholds.AFFINE_TRANS_WHOLE_DISTANCE)
return (True, True)
else:
logger.info(
"===> NO-MATCH! permutation %s score:%0.4f (thresh ca %0.4f)",
matching_permuations, round(error, 4),
thresholds.AFFINE_TRANS_WHOLE_DISTANCE)
return (True, False)
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()