aparnah/aubome
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

changed config file

Browse Source
This commit is contained in:
aparnah 2024-07-16 15:24:24 +05:30
parent 32056be80a
commit 4cdc6e0380
4 changed files with 313 additions and 137 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

68
config.yml
View File

@ -1,57 +1,15 @@
measurements: measurements:
- name: arm_length
landmarks:
- 11
- 13
- 15
- name: leg_length
landmarks:
- 23
- 25
- 27
- name: shoulder_length - name: shoulder_length
landmarks: landmarks:
- 11 - left_shoulder
- 12 - right_shoulder
- name: arm_length
- name: neck_to_hip_length landmarks:
landmarks: - left_shoulder
- 11 - left_elbow
- 23 - left_wrist
- name: leg_length
#0 - nose landmarks:
#1 - left eye (inner) - left_hip
#2 - left eye - left_knee
#3 - left eye (outer) - left_ankle
#4 - right eye (inner)
#5 - right eye
#6 - right eye (outer)
#7 - left ear
#8 - right ear
#9 - mouth (left)
#10 - mouth (right)
#11 - left shoulder
#12 - right shoulder
#13 - left elbow
#14 - right elbow
#15 - left wrist
#16 - right wrist
#17 - left pinky
#18 - right pinky
#19 - left index
#20 - right index
#21 - left thumb
#22 - right thumb
#23 - left hip
#24 - right hip
#25 - left knee
#26 - right knee
#27 - left ankle
#28 - right ankle
#29 - left heel
#30 - right heel
#31 - left foot index
#32 - right foot index

10
dockerfile
View File

@ -1,10 +0,0 @@
FROM python:3.10-slim
WORKDIR /app
COPY . /app
RUN pip install --no-cache-dir -r requirements.txt
RUN apt-get update && apt-get install ffmpeg libsm6 libxext6 -y
ENTRYPOINT ["sh", "-c", "python3 landmarks.py \"$@\" 2>&1 | grep -vE '^(WARNING:|I0000|INFO:)' | awk '{print}'", "--"]

218
landmarks.js Normal file
View File

@ -0,0 +1,218 @@
const fs = require('fs');
const path = require('path');
const ArgumentParser = require('argparse');
const cv = require('opencv');
const yaml = require('js-yaml');
const { Pose, POSE_LANDMARKS } = require('@mediapipe/pose');
const logging = console;
const warnings = console;
class Landmarker {
static resizedHeight = 256;
static resizedWidth = 256;
constructor() {
this.args = this.parseArgs();
this.measurements = this.loadLandmarks();
if (!this.args.frontImage) {
throw new Error("Front image needs to be passed");
}
if (!this.args.sideImage) {
throw new Error("Side image needs to be passed");
}
this.frontImage = cv.imread(this.args.frontImage);
this.sideImage = cv.imread(this.args.sideImage);
this.frontImageResized = this.frontImage.resize(Landmarker.resizedHeight, Landmarker.resizedWidth);
this.sideImageResized = this.sideImage.resize(Landmarker.resizedHeight, Landmarker.resizedWidth);
this.distances = {};
this.personHeight = this.args.personHeight;
this.pixelHeight = this.args.pixelHeight;
this.pose = new Pose({
locateFile: (file) => {
return `https://cdn.jsdelivr.net/npm/@mediapipe/pose/${file}`;
}
});
this.landmarksIndices = [
POSE_LANDMARKS.LEFT_SHOULDER,
POSE_LANDMARKS.RIGHT_SHOULDER,
POSE_LANDMARKS.LEFT_ELBOW,
POSE_LANDMARKS.RIGHT_ELBOW,
POSE_LANDMARKS.LEFT_WRIST,
POSE_LANDMARKS.RIGHT_WRIST,
POSE_LANDMARKS.LEFT_HIP,
POSE_LANDMARKS.RIGHT_HIP,
POSE_LANDMARKS.LEFT_KNEE,
POSE_LANDMARKS.RIGHT_KNEE,
POSE_LANDMARKS.LEFT_ANKLE,
POSE_LANDMARKS.RIGHT_ANKLE
];
}
loadLandmarks() {
const file = fs.readFileSync(this.args.yamlFile, 'utf8');
const landmarksData = yaml.load(file);
const measurements = {};
for (const measurement of landmarksData.measurements) {
measurements[measurement.name] = measurement.landmarks;
}
return measurements;
}
parseArgs() {
const parser = new ArgumentParser();
parser.add_argument('--front', { dest: 'frontImage', type: 'str', help: 'Front image' });
parser.add_argument('--side', { dest: 'sideImage', type: 'str', help: 'Side image' });
parser.add_argument('--poseDetectionConfidence', { dest: 'poseDetectionConfidence', default: 0.5, type: 'float', help: 'Confidence score for pose detection' });
parser.add_argument('--poseTrackingConfidence', { dest: 'poseTrackingConfidence', default: 0.5, type: 'float', help: 'Confidence score for pose tracking' });
parser.add_argument('--personHeight', { dest: 'personHeight', type: 'int', help: 'Person height in cm' });
parser.add_argument('--pixelHeight', { dest: 'pixelHeight', type: 'int', help: 'Pixel height of person' });
parser.add_argument('--measurement', { dest: 'measurement', nargs: '+', type: 'str', help: 'Type of measurement' });
parser.add_argument('--yamlFile', { dest: 'yamlFile', type: 'str', help: 'Path to the YAML file containing landmarks' });
return parser.parse_args();
}
async run() {
await this.pose.initialize();
const { frontResults, sideResults } = await this.processImages();
this.getCenterTopPoint(sideResults);
const table = [];
if (this.args.measurement) {
for (const m of this.args.measurement) {
if (!this.measurements[m]) {
throw new Error("Incorrect input (input not present in config.yml)");
} else {
const distance = this.calculateDistanceBetweenLandmarks(frontResults, m);
table.push([m, distance]);
}
}
} else {
for (const m in this.measurements) {
const distance = this.calculateDistanceBetweenLandmarks(frontResults, m);
table.push([m, distance]);
}
}
console.table(table);
this.pose.close();
}
async processImages() {
const frontResults = await this.pose.estimatePoses(this.frontImageResized);
const sideResults = await this.pose.estimatePoses(this.sideImageResized);
this.sideImageKeypoints = this.sideImageResized.copy();
this.frontImageKeypoints = this.frontImageResized.copy();
if (frontResults[0].landmarks) {
this.drawLandmarks(this.frontImageKeypoints, frontResults[0].landmarks, this.landmarksIndices);
}
if (sideResults[0].landmarks) {
this.drawLandmarks(this.sideImageKeypoints, sideResults[0].landmarks, this.landmarksIndices);
}
return {
frontResults: frontResults[0],
sideResults: sideResults[0]
};
}
pixelToMetricRatio() {
this.pixelHeight = this.pixelDistance * 2;
const pixelToMetricRatio = this.personHeight / this.pixelHeight;
logging.debug("pixelToMetricRatio %s", pixelToMetricRatio);
return pixelToMetricRatio;
}
drawLandmarks(image, landmarks, indices) {
for (const idx of indices) {
const landmark = landmarks[idx];
const h = image.rows;
const w = image.cols;
const cx = Math.round(landmark.x * w);
const cy = Math.round(landmark.y * h);
this.circle(image, cx, cy);
}
}
circle(image, cx, cy) {
return image.drawCircle(new cv.Point(cx, cy), 2, new cv.Vec(255, 0, 0), -1);
}
calculateDistanceBetweenLandmarks(frontResults, measurementName) {
if (!frontResults.landmarks) {
return;
}
const landmarks = frontResults.landmarks;
const landmarkNames = this.measurements[measurementName];
let totalDistance = 0;
for (let i = 0; i < landmarkNames.length - 1; i++) {
const current = landmarks[landmarkNames[i]];
const next = landmarks[landmarkNames[i + 1]];
const pixelDistance = this.euclideanDistance(
current.x * Landmarker.resizedWidth,
current.y * Landmarker.resizedHeight,
next.x * Landmarker.resizedWidth,
next.y * Landmarker.resizedHeight
);
const realDistance = pixelDistance * this.pixelToMetricRatio();
totalDistance += realDistance;
}
return totalDistance;
}
euclideanDistance(x1, y1, x2, y2) {
return Math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2);
}
getCenterTopPoint(sideResults) {
const grayImage = this.sideImageKeypoints.cvtColor(cv.COLOR_BGR2GRAY);
const blurredImage = grayImage.gaussianBlur(new cv.Size(5, 5), 0);
const roi = blurredImage.getRegion(new cv.Rect(0, 0, this.sideImageResized.cols, Math.floor(this.sideImageResized.rows / 2)));
this.edges = roi.canny(50, 150);
const contours = this.edges.findContours(cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE);
let xt, yt;
this.topmostPoint = null;
if (contours.length > 0) {
const largestContour = contours.sort((a, b) => b.area - a.area)[0];
this.topmostPoint = largestContour.minBy(pt => pt.y);
xt = this.topmostPoint.x;
yt = this.topmostPoint.y;
this.circle(this.sideImageKeypoints, xt, yt);
}
let xc, yc;
if (sideResults.landmarks) {
const leftHip = sideResults.landmarks[POSE_LANDMARKS.LEFT_HIP];
const rightHip = sideResults.landmarks[POSE_LANDMARKS.RIGHT_HIP];
const centerPoint = [
(leftHip.x + rightHip.x) / 2,
(leftHip.y + rightHip.y) / 2
];
xc = Math.round(centerPoint[0] * this.sideImageResized.cols);
yc = Math.round(centerPoint[1] * this.sideImageResized.rows);
this.circle(this.sideImageKeypoints, xc, yc);
}
this.pixelDistance = this.euclideanDistance(xt, yt, xc, yc);
this.pixelDistance *= 2;
}
}
(async () => {
const landmarker = new Landmarker();
await landmarker.run();
})();

154
landmarks.py
View File

@ -18,6 +18,41 @@ warnings.filterwarnings(
module="google.protobuf", module="google.protobuf",
) )
LANDMARK_NAME_TO_INDEX = {
"nose": 0,
"left_eye_inner": 1,
"left_eye": 2,
"left_eye_outer": 3,
"right_eye_inner": 4,
"right_eye": 5,
"right_eye_outer": 6,
"left_ear": 7,
"right_ear": 8,
"mouth_left": 9,
"mouth_right": 10,
"left_shoulder": 11,
"right_shoulder": 12,
"left_elbow": 13,
"right_elbow": 14,
"left_wrist": 15,
"right_wrist": 16,
"left_pinky": 17,
"right_pinky": 18,
"left_index": 19,
"right_index": 20,
"left_thumb": 21,
"right_thumb": 22,
"left_hip": 23,
"right_hip": 24,
"left_knee": 25,
"right_knee": 26,
"left_ankle": 27,
"right_ankle": 28,
"left_heel": 29,
"right_heel": 30,
"left_foot_index": 31,
"right_foot_index": 32,
}
class Landmarker: class Landmarker:
@ -50,18 +85,18 @@ class Landmarker:
) )
self.landmarks_indices = [ self.landmarks_indices = [
pose.PoseLandmark.LEFT_SHOULDER.value, LANDMARK_NAME_TO_INDEX["left_shoulder"],
pose.PoseLandmark.RIGHT_SHOULDER.value, LANDMARK_NAME_TO_INDEX["right_shoulder"],
pose.PoseLandmark.LEFT_ELBOW.value, LANDMARK_NAME_TO_INDEX["left_elbow"],
pose.PoseLandmark.RIGHT_ELBOW.value, LANDMARK_NAME_TO_INDEX["right_elbow"],
pose.PoseLandmark.LEFT_WRIST.value, LANDMARK_NAME_TO_INDEX["left_wrist"],
pose.PoseLandmark.RIGHT_WRIST.value, LANDMARK_NAME_TO_INDEX["right_wrist"],
pose.PoseLandmark.LEFT_HIP.value, LANDMARK_NAME_TO_INDEX["left_hip"],
pose.PoseLandmark.RIGHT_HIP.value, LANDMARK_NAME_TO_INDEX["right_hip"],
pose.PoseLandmark.LEFT_KNEE.value, LANDMARK_NAME_TO_INDEX["left_knee"],
pose.PoseLandmark.RIGHT_KNEE.value, LANDMARK_NAME_TO_INDEX["right_knee"],
pose.PoseLandmark.LEFT_ANKLE.value, LANDMARK_NAME_TO_INDEX["left_ankle"],
pose.PoseLandmark.RIGHT_ANKLE.value, LANDMARK_NAME_TO_INDEX["right_ankle"],
] ]
def load_landmarks(self): def load_landmarks(self):
@ -69,7 +104,7 @@ class Landmarker:
landmarks_data = yaml.safe_load(file) landmarks_data = yaml.safe_load(file)
measurements = {} measurements = {}
for measurement in landmarks_data["measurements"]: for measurement in landmarks_data["measurements"]:
measurements[measurement["name"]] = measurement["landmarks"] measurements[measurement["name"]] = [LANDMARK_NAME_TO_INDEX[l] for l in measurement["landmarks"]]
return measurements return measurements
def parse_args(self): def parse_args(self):
@ -257,66 +292,41 @@ class Landmarker:
] ]
self.edges = cv2.Canny(roi, 50, 150) self.edges = cv2.Canny(roi, 50, 150)
contours, _ = cv2.findContours( contours, _ = cv2.findContours(
self.edges, self.edges.copy(),
cv2.RETR_EXTERNAL, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE, cv2.CHAIN_APPROX_SIMPLE,
) )
xt, yt = None, None max_contour = max(contours, key=cv2.contourArea)
self.topmost_point = None rect = cv2.minAreaRect(max_contour)
box = cv2.boxPoints(rect)
box = sorted(
list(box),
key=lambda p: p[1],
)
top_point = min(
box[0],
box[1],
key=lambda p: p[0],
)
if contours: left_hip = side_results.pose_landmarks.landmark[LANDMARK_NAME_TO_INDEX["left_hip"]]
largest_contour = max( right_hip = side_results.pose_landmarks.landmark[LANDMARK_NAME_TO_INDEX["right_hip"]]
contours,
key=cv2.contourArea, center_x = (left_hip.x + right_hip.x) / 2
) center_y = (left_hip.y + right_hip.y) / 2
self.topmost_point = tuple(largest_contour[largest_contour[:, :, 1].argmin()][0])
xt, yt = self.topmost_point center_x, center_y = (
int(center_x * self.resized_width),
cv2.circle( int(center_y * self.resized_height),
self.side_image_keypoints, )
(xt, yt),
2, self.pixel_distance = self.euclidean_distance(
(255, 255, 0), top_point[0],
-1, top_point[1],
) center_x,
xc, yc = None, None center_y,
landmarks = side_results.pose_landmarks.landmark )
if side_results.pose_landmarks:
left_hip = landmarks[pose.PoseLandmark.LEFT_HIP.value]
right_hip = landmarks[pose.PoseLandmark.RIGHT_HIP.value]
center_point = (
(left_hip.x + right_hip.x) / 2,
(left_hip.y + right_hip.y) / 2,
)
center_point = (
int(center_point[0] * self.side_image_resized.shape[1]),
int(center_point[1] * self.side_image_resized.shape[0]),
)
xc, yc = center_point
self.circle(
self.side_image_keypoints,
xc,
yc,
)
self.pixel_distance = self.euclidean_distance(xc, yc, xt, yt)
logging.debug(
"top_center_pixel_distance: %s",
self.pixel_distance,
)
self.pixel_height = self.pixel_distance * 2
logging.debug(
"pixel height: %s ",
self.pixel_height,
)
self.distance = self.euclidean_distance(xc, yc, xt, yt) * self.pixel_to_metric_ratio()
return self.distance
l = Landmarker()
try:
l.run()
except Exception as e:
print(e)
if __name__ == "__main__":
landmarker = Landmarker()
landmarker.run()