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refactor: add missing interpolators for the string in logging

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Aparna Hatte 2024-06-17 14:40:21 +05:30
parent 7ffdaaca26
commit 5c4136cf6b
1 changed files with 33 additions and 39 deletions
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68
landmarks.py
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@ -1,9 +1,7 @@
import warnings import warnings
import os import os
warnings.filterwarnings("ignore", warnings.filterwarnings("ignore", category=UserWarning, module="google.protobuf")
category=UserWarning,
module="google.protobuf")
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
@ -30,9 +28,11 @@ class Landmarker:
self.side_image = cv2.imread(args.side_image) self.side_image = cv2.imread(args.side_image)
self.front_image_resized = cv2.resize( self.front_image_resized = cv2.resize(
self.front_image, (self.resized_height, self.resized_width)) self.front_image, (self.resized_height, self.resized_width)
)
self.side_image_resized = cv2.resize( self.side_image_resized = cv2.resize(
self.side_image, (self.resized_height, self.resized_width)) self.side_image, (self.resized_height, self.resized_width)
)
self.person_height = args.person_height self.person_height = args.person_height
self.pixel_height = args.pixel_height self.pixel_height = args.pixel_height
@ -60,14 +60,8 @@ class Landmarker:
def parse_args(self): def parse_args(self):
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument("--front", parser.add_argument("--front", dest="front_image", type=str, help="Front image")
dest="front_image", parser.add_argument("--side", dest="side_image", type=str, help="Side image")
type=str,
help="Front image")
parser.add_argument("--side",
dest="side_image",
type=str,
help="Side image")
parser.add_argument( parser.add_argument(
"--pose_detection_confidence", "--pose_detection_confidence",
dest="pose_detection_confidence", dest="pose_detection_confidence",
@ -100,9 +94,9 @@ class Landmarker:
def run(self): def run(self):
logging.warning("person's height: ", self.person_height) logging.warning("person's height: %s", self.person_height)
logging.warning("person's pixel height: ", self.pixel_height) logging.warning("person's pixel height: %s", self.pixel_height)
front_results = self.process_images() front_results = self.process_images()
@ -118,9 +112,11 @@ class Landmarker:
def process_images(self): def process_images(self):
front_results = self.pose.process( front_results = self.pose.process(
cv2.cvtColor(self.front_image_resized, cv2.COLOR_BGR2RGB)) cv2.cvtColor(self.front_image_resized, cv2.COLOR_BGR2RGB)
)
side_results = self.pose.process( side_results = self.pose.process(
cv2.cvtColor(self.side_image_resized, cv2.COLOR_BGR2RGB)) cv2.cvtColor(self.side_image_resized, cv2.COLOR_BGR2RGB)
)
self.side_image_keypoints = self.side_image_resized.copy() self.side_image_keypoints = self.side_image_resized.copy()
self.front_image_keypoints = self.front_image_resized.copy() self.front_image_keypoints = self.front_image_resized.copy()
@ -153,7 +149,7 @@ class Landmarker:
def pixel_to_metric_ratio(self): def pixel_to_metric_ratio(self):
self.pixel_height = self.pixel_distance * 2 self.pixel_height = self.pixel_distance * 2
pixel_to_metric_ratio = self.person_height / self.pixel_height pixel_to_metric_ratio = self.person_height / self.pixel_height
logging.warning("pixel_to_metric_ratio", pixel_to_metric_ratio) logging.warning("pixel_to_metric_ratio %s", pixel_to_metric_ratio)
return pixel_to_metric_ratio return pixel_to_metric_ratio
def draw_landmarks(self, image, landmarks, indices): def draw_landmarks(self, image, landmarks, indices):
@ -200,17 +196,13 @@ class Landmarker:
knee_left = landmarks[pose.PoseLandmark.LEFT_KNEE.value] knee_left = landmarks[pose.PoseLandmark.LEFT_KNEE.value]
ankle_left = landmarks[pose.PoseLandmark.LEFT_ANKLE.value] ankle_left = landmarks[pose.PoseLandmark.LEFT_ANKLE.value]
self.distance_left_hand_up = self.calculate_distance( self.distance_left_hand_up = self.calculate_distance(shoulder_left, elbow_left)
shoulder_left, elbow_left)
self.distance_left_hand_down = self.calculate_distance( self.distance_left_hand_down = self.calculate_distance(elbow_left, wrist_left)
elbow_left, wrist_left)
self.distance_left_leg_up = self.calculate_distance( self.distance_left_leg_up = self.calculate_distance(hip_left, knee_left)
hip_left, knee_left)
self.distance_left_leg_down = self.calculate_distance( self.distance_left_leg_down = self.calculate_distance(knee_left, ankle_left)
knee_left, ankle_left)
def euclidean_distance(self, x1, x2, y1, y2): def euclidean_distance(self, x1, x2, y1, y2):
distance = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2) distance = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
@ -226,25 +218,26 @@ class Landmarker:
cv2.waitKey(0) cv2.waitKey(0)
def get_center_top_point(self, side_results): def get_center_top_point(self, side_results):
gray_image = cv2.cvtColor(self.side_image_keypoints, gray_image = cv2.cvtColor(self.side_image_keypoints, cv2.COLOR_BGR2GRAY)
cv2.COLOR_BGR2GRAY)
blurred_image = cv2.GaussianBlur(gray_image, (5, 5), 0) blurred_image = cv2.GaussianBlur(gray_image, (5, 5), 0)
roi = blurred_image[0 : int(self.side_image_resized.shape[0] / 2), :] roi = blurred_image[0 : int(self.side_image_resized.shape[0] / 2), :]
self.edges = cv2.Canny(roi, 50, 150) self.edges = cv2.Canny(roi, 50, 150)
contours, _ = cv2.findContours(self.edges, cv2.RETR_EXTERNAL, contours, _ = cv2.findContours(
cv2.CHAIN_APPROX_SIMPLE) self.edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
)
xt, yt = None, None xt, yt = None, None
self.topmost_point = None self.topmost_point = None
if contours: if contours:
largest_contour = max(contours, key=cv2.contourArea) largest_contour = max(contours, key=cv2.contourArea)
self.topmost_point = tuple( self.topmost_point = tuple(
largest_contour[largest_contour[:, :, 1].argmin()][0]) largest_contour[largest_contour[:, :, 1].argmin()][0]
)
xt, yt = self.topmost_point xt, yt = self.topmost_point
self.circle(self.side_image_keypoints, xt, yt) self.circle(self.side_image_keypoints, xt, yt)
logging.warning("xt: ", xt) logging.warning("xt: %s", xt)
logging.warning(f"yt: ") logging.warning("yt: %s", yt)
xc, yc = None, None xc, yc = None, None
landmarks = side_results.pose_landmarks.landmark landmarks = side_results.pose_landmarks.landmark
@ -260,13 +253,14 @@ class Landmarker:
int(center_point[1] * self.side_image_resized.shape[0]), int(center_point[1] * self.side_image_resized.shape[0]),
) )
xc, yc = center_point xc, yc = center_point
logging.warning("xc: ", xc) logging.warning("xc: %s", xc)
logging.warning(f"yc: {yc}") logging.warning("yc: %s", yc)
self.circle(self.side_image_keypoints, xc, yc) self.circle(self.side_image_keypoints, xc, yc)
self.pixel_distance = self.euclidean_distance(xc, xt, yc, yt) self.pixel_distance = self.euclidean_distance(xc, xt, yc, yt)
self.distance = self.euclidean_distance( self.distance = (
xc, xt, yc, yt) * self.pixel_to_metric_ratio() self.euclidean_distance(xc, xt, yc, yt) * self.pixel_to_metric_ratio()
)
return self.distance return self.distance