refactor: reify code
This commit is contained in:
parent
5af7cf3ee8
commit
3a263937ab
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@ -9,13 +9,13 @@ if TYPE_CHECKING:
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from environment import Environment
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from environment import Environment
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class Head:
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class BodyPart:
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"""The head body part."""
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"""A basic body part."""
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def __init__(self, env: Environment) -> None:
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def __init__(self, env: Environment, image_path: str, position, height) -> None:
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"""Initialize the head."""
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"""Initialize the part."""
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self.env = env
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self.env = env
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self.image = cv2.imread("assets/head.png", cv2.IMREAD_UNCHANGED)
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self.image = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.bounding_box = np.array(
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self.bounding_box = np.array(
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[
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[
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@ -28,24 +28,33 @@ class Head:
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)
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)
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self.old_box = np.zeros((4, 1, 2))
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self.old_box = np.zeros((4, 1, 2))
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self.position = position
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self.height = height
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def draw(self) -> None:
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def draw(self) -> None:
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"""Draw the head on the screen."""
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"""Draw the part on the screen."""
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# compute position
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# compute position
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if self.env.results.multi_face_landmarks:
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if self.env.results.multi_face_landmarks:
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x = self.env.x - self.env.model_points[0]
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x = self.env.x
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y = self.env.y - self.env.model_points[0]
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y = self.env.y
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for face_landmarks in self.env.results.multi_face_landmarks:
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for face_landmarks in self.env.results.multi_face_landmarks:
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head_box = np.array(
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# compute bounding box from position and height
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[
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head_box = (
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self.ratio * x + y + self.env.model_points[0],
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np.array(
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self.ratio * -x + y + self.env.model_points[0],
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[
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self.ratio * -x + -y + self.env.model_points[0],
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self.ratio * x * self.height + y * self.height,
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self.ratio * x + -y + self.env.model_points[0],
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self.ratio * -x * self.height + y * self.height,
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]
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self.ratio * -x * self.height + -y * self.height,
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self.ratio * x * self.height + -y * self.height,
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]
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)
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+ self.position
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+ self.env.center
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)
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)
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# project bounding box to camera
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(box, _) = cv2.projectPoints(
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(box, _) = cv2.projectPoints(
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head_box,
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head_box,
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self.env.mp_rotation_vector,
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self.env.mp_rotation_vector,
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@ -58,12 +67,6 @@ class Head:
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box = (box + self.old_box) / 2
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box = (box + self.old_box) / 2
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self.old_box = box
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self.old_box = box
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a, b, c, d = box.squeeze().astype(int)
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cv2.line(self.env.frame, a, b, (255, 255, 255), 2)
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cv2.line(self.env.frame, b, c, (255, 255, 255), 2)
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cv2.line(self.env.frame, c, d, (255, 255, 255), 2)
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cv2.line(self.env.frame, d, a, (255, 255, 255), 2)
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# get perspective transform
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# get perspective transform
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transform_mat = cv2.getPerspectiveTransform(
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transform_mat = cv2.getPerspectiveTransform(
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self.bounding_box,
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self.bounding_box,
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@ -82,13 +85,10 @@ class Head:
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def draw_debug(self) -> None:
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def draw_debug(self) -> None:
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"""Draw debug information on the screen."""
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"""Draw debug information on the screen."""
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# link points
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cv2.polylines(
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pass
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self.env.frame,
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# for i in range(4):
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[self.old_box.squeeze().astype(int)],
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# cv2.line(
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True,
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# self.env.frame,
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(255, 255, 255),
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# tuple(self.translated_head_box[i].astype(np.int32)),
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2,
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# tuple(self.translated_head_box[(i + 1) % 4].astype(np.int32)),
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)
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# (255, 255, 255),
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# 2,
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# )
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@ -1,9 +0,0 @@
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from .crown import Crown
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from .head import Head
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from .left_ear import LeftEar
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from .left_eye import LeftEye
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from .left_moustache import LeftMoustache
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from .mouth import Mouth
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from .right_ear import RightEar
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from .right_eye import RightEye
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from .right_moustache import RightMoustache
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@ -1,74 +0,0 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import cv2
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import numpy as np
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if TYPE_CHECKING:
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from environment import Environment
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class Crown:
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"""The crown body part."""
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def __init__(self, env: Environment) -> None:
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"""Initialize the crown."""
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self.env = env
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self.image = cv2.imread("assets/crown.png", cv2.IMREAD_UNCHANGED)
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.bouding_box = np.array(
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[
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[0, 0],
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[self.image.shape[1], 0],
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[self.image.shape[1], self.image.shape[0]],
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[0, self.image.shape[0]],
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],
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dtype=np.float32,
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)
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def draw(self) -> None:
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"""Draw the crown on the screen."""
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# compute position
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if self.env.results.multi_face_landmarks:
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for face_landmarks in self.env.results.multi_face_landmarks:
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box = np.array(
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[
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30 * self.ratio * self.env.x + 135 * self.env.y + 90 * self.env.z,
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-30 * self.ratio * self.env.x + 135 * self.env.y + 90 * self.env.z,
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-30 * self.ratio * self.env.x + 75 * self.env.y + 90 * self.env.z,
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30 * self.ratio * self.env.x + 75 * self.env.y + 90 * self.env.z,
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]
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)[:, :2]
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self.translated_box = (
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box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
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).astype(np.float32)
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# get perspective transform
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transform_mat = cv2.getPerspectiveTransform(
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self.bouding_box,
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self.translated_box,
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)
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# apply perspective transform to image
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warped = cv2.warpPerspective(
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self.image,
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transform_mat,
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self.env.frame.shape[1::-1],
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)
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# replace non black pixels of warped image by frame
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self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
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def draw_debug(self) -> None:
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"""Draw debug information on the screen."""
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# link points
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for i in range(4):
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cv2.line(
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self.env.frame,
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tuple(self.translated_box[i].astype(np.int32)),
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tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
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(255, 255, 255),
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2,
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)
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@ -1,74 +0,0 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import cv2
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import numpy as np
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if TYPE_CHECKING:
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from environment import Environment
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class LeftEar:
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"""The left eye body part."""
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def __init__(self, env: Environment) -> None:
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"""Initialize the left eye."""
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self.env = env
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self.image = cv2.imread("assets/earL.png", cv2.IMREAD_UNCHANGED)
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.bouding_box = np.array(
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[
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[0, 0],
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[self.image.shape[1], 0],
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[self.image.shape[1], self.image.shape[0]],
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[0, self.image.shape[0]],
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],
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dtype=np.float32,
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)
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def draw(self) -> None:
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"""Draw the left eye on the screen."""
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# compute position
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if self.env.results.multi_face_landmarks:
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for face_landmarks in self.env.results.multi_face_landmarks:
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box = np.array(
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[
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100 * self.env.x + 250 * self.env.y + 70 * self.env.z,
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30 * self.env.x + 250 * self.env.y + 70 * self.env.z,
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30 * self.env.x + 50 * self.env.y + 70 * self.env.z,
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100 * self.env.x + 50 * self.env.y + 70 * self.env.z,
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]
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)[:, :2]
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self.translated_box = (
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box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
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).astype(np.float32)
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# get perspective transform
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transform_mat = cv2.getPerspectiveTransform(
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self.bouding_box,
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self.translated_box,
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)
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# apply perspective transform to image
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warped = cv2.warpPerspective(
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self.image,
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transform_mat,
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self.env.frame.shape[1::-1],
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)
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# replace non black pixels of warped image by frame
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self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
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def draw_debug(self) -> None:
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"""Draw debug information on the screen."""
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# link points
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for i in range(4):
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cv2.line(
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self.env.frame,
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tuple(self.translated_box[i].astype(np.int32)),
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tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
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(255, 255, 255),
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2,
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)
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@ -1,74 +0,0 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import cv2
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import numpy as np
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if TYPE_CHECKING:
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from environment import Environment
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class LeftEye:
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"""The left eye body part."""
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def __init__(self, env: Environment) -> None:
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"""Initialize the left eye."""
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self.env = env
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self.image = cv2.imread("assets/eyeL.png", cv2.IMREAD_UNCHANGED)
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.bouding_box = np.array(
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[
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[0, 0],
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[self.image.shape[1], 0],
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[self.image.shape[1], self.image.shape[0]],
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[0, self.image.shape[0]],
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],
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dtype=np.float32,
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)
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def draw(self) -> None:
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"""Draw the left eye on the screen."""
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# compute position
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if self.env.results.multi_face_landmarks:
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for face_landmarks in self.env.results.multi_face_landmarks:
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box = np.array(
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[
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40 * self.env.x + 70 * self.env.y + 80 * self.env.z,
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25 * self.env.x + 70 * self.env.y + 80 * self.env.z,
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25 * self.env.x + 15 * self.env.y + 80 * self.env.z,
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40 * self.env.x + 15 * self.env.y + 80 * self.env.z,
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]
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)[:, :2]
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self.translated_box = (
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box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
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).astype(np.float32)
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# get perspective transform
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transform_mat = cv2.getPerspectiveTransform(
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self.bouding_box,
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self.translated_box,
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)
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# apply perspective transform to image
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warped = cv2.warpPerspective(
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self.image,
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transform_mat,
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self.env.frame.shape[1::-1],
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)
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# replace non black pixels of warped image by frame
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self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
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def draw_debug(self) -> None:
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"""Draw debug information on the screen."""
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# link points
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for i in range(4):
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cv2.line(
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self.env.frame,
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tuple(self.translated_box[i].astype(np.int32)),
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tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
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(255, 255, 255),
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2,
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)
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@ -1,74 +0,0 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import cv2
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import numpy as np
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if TYPE_CHECKING:
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from environment import Environment
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class LeftMoustache:
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"""The left eye body part."""
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def __init__(self, env: Environment) -> None:
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"""Initialize the left eye."""
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self.env = env
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self.image = cv2.imread("assets/moustacheL.png", cv2.IMREAD_UNCHANGED)
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self.ratio = self.image.shape[1] / self.image.shape[0]
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self.bouding_box = np.array(
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[
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[0, 0],
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[self.image.shape[1], 0],
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[self.image.shape[1], self.image.shape[0]],
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[0, self.image.shape[0]],
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],
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dtype=np.float32,
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)
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def draw(self) -> None:
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"""Draw the left eye on the screen."""
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# compute position
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if self.env.results.multi_face_landmarks:
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for face_landmarks in self.env.results.multi_face_landmarks:
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box = np.array(
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[
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270 * self.env.x + 20 * self.env.y + 80 * self.env.z,
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70 * self.env.x + 20 * self.env.y + 80 * self.env.z,
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70 * self.env.x + -130 * self.env.y + 80 * self.env.z,
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270 * self.env.x + -130 * self.env.y + 80 * self.env.z,
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]
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)[:, :2]
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self.translated_box = (
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box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
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).astype(np.float32)
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# get perspective transform
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transform_mat = cv2.getPerspectiveTransform(
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self.bouding_box,
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self.translated_box,
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)
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# apply perspective transform to image
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|
||||||
warped = cv2.warpPerspective(
|
|
||||||
self.image,
|
|
||||||
transform_mat,
|
|
||||||
self.env.frame.shape[1::-1],
|
|
||||||
)
|
|
||||||
|
|
||||||
# replace non black pixels of warped image by frame
|
|
||||||
self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
|
|
||||||
|
|
||||||
def draw_debug(self) -> None:
|
|
||||||
"""Draw debug information on the screen."""
|
|
||||||
# link points
|
|
||||||
for i in range(4):
|
|
||||||
cv2.line(
|
|
||||||
self.env.frame,
|
|
||||||
tuple(self.translated_box[i].astype(np.int32)),
|
|
||||||
tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
|
|
||||||
(255, 255, 255),
|
|
||||||
2,
|
|
||||||
)
|
|
|
@ -1,74 +0,0 @@
|
||||||
from __future__ import annotations
|
|
||||||
|
|
||||||
from typing import TYPE_CHECKING
|
|
||||||
|
|
||||||
import cv2
|
|
||||||
import numpy as np
|
|
||||||
|
|
||||||
if TYPE_CHECKING:
|
|
||||||
from environment import Environment
|
|
||||||
|
|
||||||
|
|
||||||
class Mouth:
|
|
||||||
"""The mouth body part."""
|
|
||||||
|
|
||||||
def __init__(self, env: Environment) -> None:
|
|
||||||
"""Initialize the mouth."""
|
|
||||||
self.env = env
|
|
||||||
self.image = cv2.imread("assets/mouth.png", cv2.IMREAD_UNCHANGED)
|
|
||||||
self.ratio = self.image.shape[1] / self.image.shape[0]
|
|
||||||
self.bouding_box = np.array(
|
|
||||||
[
|
|
||||||
[0, 0],
|
|
||||||
[self.image.shape[1], 0],
|
|
||||||
[self.image.shape[1], self.image.shape[0]],
|
|
||||||
[0, self.image.shape[0]],
|
|
||||||
],
|
|
||||||
dtype=np.float32,
|
|
||||||
)
|
|
||||||
|
|
||||||
def draw(self) -> None:
|
|
||||||
"""Draw the mouth on the screen."""
|
|
||||||
# compute position
|
|
||||||
if self.env.results.multi_face_landmarks:
|
|
||||||
for face_landmarks in self.env.results.multi_face_landmarks:
|
|
||||||
box = np.array(
|
|
||||||
[
|
|
||||||
15 * self.ratio * self.env.x + -30 * self.env.y + 80 * self.env.z,
|
|
||||||
-15 * self.ratio * self.env.x + -30 * self.env.y + 80 * self.env.z,
|
|
||||||
-15 * self.ratio * self.env.x + -50 * self.env.y + 80 * self.env.z,
|
|
||||||
15 * self.ratio * self.env.x + -50 * self.env.y + 80 * self.env.z,
|
|
||||||
]
|
|
||||||
)[:, :2]
|
|
||||||
|
|
||||||
self.translated_box = (
|
|
||||||
box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
|
|
||||||
).astype(np.float32)
|
|
||||||
|
|
||||||
# get perspective transform
|
|
||||||
transform_mat = cv2.getPerspectiveTransform(
|
|
||||||
self.bouding_box,
|
|
||||||
self.translated_box,
|
|
||||||
)
|
|
||||||
|
|
||||||
# apply perspective transform to image
|
|
||||||
warped = cv2.warpPerspective(
|
|
||||||
self.image,
|
|
||||||
transform_mat,
|
|
||||||
self.env.frame.shape[1::-1],
|
|
||||||
)
|
|
||||||
|
|
||||||
# replace non black pixels of warped image by frame
|
|
||||||
self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
|
|
||||||
|
|
||||||
def draw_debug(self) -> None:
|
|
||||||
"""Draw debug information on the screen."""
|
|
||||||
# link points
|
|
||||||
for i in range(4):
|
|
||||||
cv2.line(
|
|
||||||
self.env.frame,
|
|
||||||
tuple(self.translated_box[i].astype(np.int32)),
|
|
||||||
tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
|
|
||||||
(255, 255, 255),
|
|
||||||
2,
|
|
||||||
)
|
|
|
@ -1,74 +0,0 @@
|
||||||
from __future__ import annotations
|
|
||||||
|
|
||||||
from typing import TYPE_CHECKING
|
|
||||||
|
|
||||||
import cv2
|
|
||||||
import numpy as np
|
|
||||||
|
|
||||||
if TYPE_CHECKING:
|
|
||||||
from environment import Environment
|
|
||||||
|
|
||||||
|
|
||||||
class RightEar:
|
|
||||||
"""The left eye body part."""
|
|
||||||
|
|
||||||
def __init__(self, env: Environment) -> None:
|
|
||||||
"""Initialize the left eye."""
|
|
||||||
self.env = env
|
|
||||||
self.image = cv2.imread("assets/earR.png", cv2.IMREAD_UNCHANGED)
|
|
||||||
self.ratio = self.image.shape[1] / self.image.shape[0]
|
|
||||||
self.bouding_box = np.array(
|
|
||||||
[
|
|
||||||
[0, 0],
|
|
||||||
[self.image.shape[1], 0],
|
|
||||||
[self.image.shape[1], self.image.shape[0]],
|
|
||||||
[0, self.image.shape[0]],
|
|
||||||
],
|
|
||||||
dtype=np.float32,
|
|
||||||
)
|
|
||||||
|
|
||||||
def draw(self) -> None:
|
|
||||||
"""Draw the left eye on the screen."""
|
|
||||||
# compute position
|
|
||||||
if self.env.results.multi_face_landmarks:
|
|
||||||
for face_landmarks in self.env.results.multi_face_landmarks:
|
|
||||||
box = np.array(
|
|
||||||
[
|
|
||||||
-30 * self.env.x + 250 * self.env.y + 70 * self.env.z,
|
|
||||||
-100 * self.env.x + 250 * self.env.y + 70 * self.env.z,
|
|
||||||
-100 * self.env.x + 50 * self.env.y + 70 * self.env.z,
|
|
||||||
-30 * self.env.x + 50 * self.env.y + 70 * self.env.z,
|
|
||||||
]
|
|
||||||
)[:, :2]
|
|
||||||
|
|
||||||
self.translated_box = (
|
|
||||||
box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
|
|
||||||
).astype(np.float32)
|
|
||||||
|
|
||||||
# get perspective transform
|
|
||||||
transform_mat = cv2.getPerspectiveTransform(
|
|
||||||
self.bouding_box,
|
|
||||||
self.translated_box,
|
|
||||||
)
|
|
||||||
|
|
||||||
# apply perspective transform to image
|
|
||||||
warped = cv2.warpPerspective(
|
|
||||||
self.image,
|
|
||||||
transform_mat,
|
|
||||||
self.env.frame.shape[1::-1],
|
|
||||||
)
|
|
||||||
|
|
||||||
# replace non black pixels of warped image by frame
|
|
||||||
self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
|
|
||||||
|
|
||||||
def draw_debug(self) -> None:
|
|
||||||
"""Draw debug information on the screen."""
|
|
||||||
# link points
|
|
||||||
for i in range(4):
|
|
||||||
cv2.line(
|
|
||||||
self.env.frame,
|
|
||||||
tuple(self.translated_box[i].astype(np.int32)),
|
|
||||||
tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
|
|
||||||
(255, 255, 255),
|
|
||||||
2,
|
|
||||||
)
|
|
|
@ -1,74 +0,0 @@
|
||||||
from __future__ import annotations
|
|
||||||
|
|
||||||
from typing import TYPE_CHECKING
|
|
||||||
|
|
||||||
import cv2
|
|
||||||
import numpy as np
|
|
||||||
|
|
||||||
if TYPE_CHECKING:
|
|
||||||
from environment import Environment
|
|
||||||
|
|
||||||
|
|
||||||
class RightEye:
|
|
||||||
"""The right eye body part."""
|
|
||||||
|
|
||||||
def __init__(self, env: Environment) -> None:
|
|
||||||
"""Initialize the right eye."""
|
|
||||||
self.env = env
|
|
||||||
self.image = cv2.imread("assets/eyeR.png", cv2.IMREAD_UNCHANGED)
|
|
||||||
self.ratio = self.image.shape[1] / self.image.shape[0]
|
|
||||||
self.bouding_box = np.array(
|
|
||||||
[
|
|
||||||
[0, 0],
|
|
||||||
[self.image.shape[1], 0],
|
|
||||||
[self.image.shape[1], self.image.shape[0]],
|
|
||||||
[0, self.image.shape[0]],
|
|
||||||
],
|
|
||||||
dtype=np.float32,
|
|
||||||
)
|
|
||||||
|
|
||||||
def draw(self) -> None:
|
|
||||||
"""Draw the right eye on the screen."""
|
|
||||||
# compute position
|
|
||||||
if self.env.results.multi_face_landmarks:
|
|
||||||
for face_landmarks in self.env.results.multi_face_landmarks:
|
|
||||||
box = np.array(
|
|
||||||
[
|
|
||||||
-25 * self.env.x + 70 * self.env.y + 80 * self.env.z,
|
|
||||||
-40 * self.env.x + 70 * self.env.y + 80 * self.env.z,
|
|
||||||
-40 * self.env.x + 15 * self.env.y + 80 * self.env.z,
|
|
||||||
-25 * self.env.x + 15 * self.env.y + 80 * self.env.z,
|
|
||||||
]
|
|
||||||
)
|
|
||||||
|
|
||||||
self.translated_box = (
|
|
||||||
box[:, :2] + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
|
|
||||||
).astype(np.float32)
|
|
||||||
|
|
||||||
# get perspective transform
|
|
||||||
transform_mat = cv2.getPerspectiveTransform(
|
|
||||||
self.bouding_box,
|
|
||||||
self.translated_box,
|
|
||||||
)
|
|
||||||
|
|
||||||
# apply perspective transform to image
|
|
||||||
warped = cv2.warpPerspective(
|
|
||||||
self.image,
|
|
||||||
transform_mat,
|
|
||||||
self.env.frame.shape[1::-1],
|
|
||||||
)
|
|
||||||
|
|
||||||
# replace non black pixels of warped image by frame
|
|
||||||
self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
|
|
||||||
|
|
||||||
def draw_debug(self) -> None:
|
|
||||||
"""Draw debug information on the screen."""
|
|
||||||
# link points
|
|
||||||
for i in range(4):
|
|
||||||
cv2.line(
|
|
||||||
self.env.frame,
|
|
||||||
tuple(self.translated_box[i].astype(np.int32)),
|
|
||||||
tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
|
|
||||||
(255, 255, 255),
|
|
||||||
2,
|
|
||||||
)
|
|
|
@ -1,74 +0,0 @@
|
||||||
from __future__ import annotations
|
|
||||||
|
|
||||||
from typing import TYPE_CHECKING
|
|
||||||
|
|
||||||
import cv2
|
|
||||||
import numpy as np
|
|
||||||
|
|
||||||
if TYPE_CHECKING:
|
|
||||||
from environment import Environment
|
|
||||||
|
|
||||||
|
|
||||||
class RightMoustache:
|
|
||||||
"""The left eye body part."""
|
|
||||||
|
|
||||||
def __init__(self, env: Environment) -> None:
|
|
||||||
"""Initialize the left eye."""
|
|
||||||
self.env = env
|
|
||||||
self.image = cv2.imread("assets/moustacheR.png", cv2.IMREAD_UNCHANGED)
|
|
||||||
self.ratio = self.image.shape[1] / self.image.shape[0]
|
|
||||||
self.bouding_box = np.array(
|
|
||||||
[
|
|
||||||
[0, 0],
|
|
||||||
[self.image.shape[1], 0],
|
|
||||||
[self.image.shape[1], self.image.shape[0]],
|
|
||||||
[0, self.image.shape[0]],
|
|
||||||
],
|
|
||||||
dtype=np.float32,
|
|
||||||
)
|
|
||||||
|
|
||||||
def draw(self) -> None:
|
|
||||||
"""Draw the left eye on the screen."""
|
|
||||||
# compute position
|
|
||||||
if self.env.results.multi_face_landmarks:
|
|
||||||
for face_landmarks in self.env.results.multi_face_landmarks:
|
|
||||||
box = np.array(
|
|
||||||
[
|
|
||||||
-70 * self.env.x + 20 * self.env.y + 80 * self.env.z,
|
|
||||||
-270 * self.env.x + 20 * self.env.y + 80 * self.env.z,
|
|
||||||
-270 * self.env.x + -130 * self.env.y + 80 * self.env.z,
|
|
||||||
-70 * self.env.x + -130 * self.env.y + 80 * self.env.z,
|
|
||||||
]
|
|
||||||
)[:, :2]
|
|
||||||
|
|
||||||
self.translated_box = (
|
|
||||||
box + self.env.center[:2] * np.array([self.env.camera_width, self.env.camera_height])
|
|
||||||
).astype(np.float32)
|
|
||||||
|
|
||||||
# get perspective transform
|
|
||||||
transform_mat = cv2.getPerspectiveTransform(
|
|
||||||
self.bouding_box,
|
|
||||||
self.translated_box,
|
|
||||||
)
|
|
||||||
|
|
||||||
# apply perspective transform to image
|
|
||||||
warped = cv2.warpPerspective(
|
|
||||||
self.image,
|
|
||||||
transform_mat,
|
|
||||||
self.env.frame.shape[1::-1],
|
|
||||||
)
|
|
||||||
|
|
||||||
# replace non black pixels of warped image by frame
|
|
||||||
self.env.avatar[warped[:, :, 3] != 0] = warped[warped[:, :, 3] != 0][:, :3]
|
|
||||||
|
|
||||||
def draw_debug(self) -> None:
|
|
||||||
"""Draw debug information on the screen."""
|
|
||||||
# link points
|
|
||||||
for i in range(4):
|
|
||||||
cv2.line(
|
|
||||||
self.env.frame,
|
|
||||||
tuple(self.translated_box[i].astype(np.int32)),
|
|
||||||
tuple(self.translated_box[(i + 1) % 4].astype(np.int32)),
|
|
||||||
(255, 255, 255),
|
|
||||||
2,
|
|
||||||
)
|
|
|
@ -3,33 +3,12 @@ import logging
|
||||||
import cv2
|
import cv2
|
||||||
import mediapipe as mp
|
import mediapipe as mp
|
||||||
import numpy as np
|
import numpy as np
|
||||||
from mediapipe.framework.formats import landmark_pb2
|
|
||||||
|
|
||||||
from bodyparts import (
|
from bodypart import BodyPart
|
||||||
Crown,
|
from face_geometry import PCF, get_metric_landmarks
|
||||||
Head,
|
|
||||||
LeftEar,
|
|
||||||
LeftEye,
|
|
||||||
LeftMoustache,
|
|
||||||
Mouth,
|
|
||||||
RightEar,
|
|
||||||
RightEye,
|
|
||||||
RightMoustache,
|
|
||||||
)
|
|
||||||
from face_geometry import PCF, get_metric_landmarks, procrustes_landmark_basis
|
|
||||||
from utils import (
|
|
||||||
LANDMARKS_BOTTOM_SIDE,
|
|
||||||
LANDMARKS_LEFT_SIDE,
|
|
||||||
LANDMARKS_RIGHT_SIDE,
|
|
||||||
LANDMARKS_TOP_SIDE,
|
|
||||||
landmark2vec,
|
|
||||||
)
|
|
||||||
|
|
||||||
points_idx = [33, 263, 61, 291, 199]
|
NOSE_LANDMARK = 4
|
||||||
points_idx = points_idx + [key for (key, val) in procrustes_landmark_basis]
|
UNREFINED_LANDMARKS = 468
|
||||||
points_idx = list(set(points_idx))
|
|
||||||
points_idx.sort()
|
|
||||||
print(points_idx)
|
|
||||||
|
|
||||||
|
|
||||||
class Environment:
|
class Environment:
|
||||||
|
@ -50,6 +29,7 @@ class Environment:
|
||||||
self.mp_drawing = mp.solutions.drawing_utils # type: ignore
|
self.mp_drawing = mp.solutions.drawing_utils # type: ignore
|
||||||
self.mp_drawing_styles = mp.solutions.drawing_styles # type: ignore
|
self.mp_drawing_styles = mp.solutions.drawing_styles # type: ignore
|
||||||
self.mp_face_mesh = mp.solutions.face_mesh # type: ignore
|
self.mp_face_mesh = mp.solutions.face_mesh # type: ignore
|
||||||
|
self.refine_landmarks = True
|
||||||
|
|
||||||
# get screen size from webcam
|
# get screen size from webcam
|
||||||
self.camera_width = camera.get(3)
|
self.camera_width = camera.get(3)
|
||||||
|
@ -57,26 +37,64 @@ class Environment:
|
||||||
|
|
||||||
# create body parts
|
# create body parts
|
||||||
self.body_parts = [
|
self.body_parts = [
|
||||||
# LeftEar(self),
|
BodyPart(
|
||||||
# RightEar(self),
|
self,
|
||||||
Head(self),
|
"assets/earL.png",
|
||||||
# RightMoustache(self),
|
np.array([6, 11, -0.5]),
|
||||||
# LeftMoustache(self),
|
1,
|
||||||
# LeftEye(self),
|
),
|
||||||
# RightEye(self),
|
BodyPart(
|
||||||
# Crown(self),
|
self,
|
||||||
# Mouth(self),
|
"assets/earR.png",
|
||||||
|
np.array([-6, 11, -0.5]),
|
||||||
|
1,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/head.png",
|
||||||
|
np.array([0, 0, 0]),
|
||||||
|
1,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/moustacheL.png",
|
||||||
|
np.array([13, -6, 0.1]),
|
||||||
|
1,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/moustacheR.png",
|
||||||
|
np.array([-13, -6, 0.1]),
|
||||||
|
1,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/eyeL.png",
|
||||||
|
np.array([2.5, 2.5, 0.1]),
|
||||||
|
0.3,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/eyeR.png",
|
||||||
|
np.array([-2.5, 2.5, 0.1]),
|
||||||
|
0.3,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/crown.png",
|
||||||
|
np.array([0, 6.5, 0.5]),
|
||||||
|
0.3,
|
||||||
|
),
|
||||||
|
BodyPart(
|
||||||
|
self,
|
||||||
|
"assets/mouth.png",
|
||||||
|
np.array([0, -3.5, 0.1]),
|
||||||
|
0.15,
|
||||||
|
),
|
||||||
]
|
]
|
||||||
|
|
||||||
self.pcf = PCF(
|
|
||||||
near=1,
|
|
||||||
far=10000,
|
|
||||||
frame_height=self.camera_height,
|
|
||||||
frame_width=self.camera_width,
|
|
||||||
fy=self.camera_width,
|
|
||||||
)
|
|
||||||
|
|
||||||
# pseudo camera internals
|
# pseudo camera internals
|
||||||
|
self.dist_coeff = np.zeros((4, 1))
|
||||||
self.focal_length = self.camera_width
|
self.focal_length = self.camera_width
|
||||||
self.center = (self.camera_width / 2, self.camera_height / 2)
|
self.center = (self.camera_width / 2, self.camera_height / 2)
|
||||||
self.camera_matrix = np.array(
|
self.camera_matrix = np.array(
|
||||||
|
@ -87,10 +105,13 @@ class Environment:
|
||||||
],
|
],
|
||||||
dtype="double",
|
dtype="double",
|
||||||
)
|
)
|
||||||
|
self.pcf = PCF(
|
||||||
self.dist_coeff = np.zeros((4, 1))
|
near=1,
|
||||||
|
far=10000,
|
||||||
self.refine_landmarks = True
|
frame_height=self.camera_height,
|
||||||
|
frame_width=self.camera_width,
|
||||||
|
fy=self.focal_length,
|
||||||
|
)
|
||||||
|
|
||||||
def start(self) -> None:
|
def start(self) -> None:
|
||||||
"""Start the environment."""
|
"""Start the environment."""
|
||||||
|
@ -155,41 +176,46 @@ class Environment:
|
||||||
def compute_face_axis(self) -> None:
|
def compute_face_axis(self) -> None:
|
||||||
"""Compute the face axis."""
|
"""Compute the face axis."""
|
||||||
if self.results.multi_face_landmarks:
|
if self.results.multi_face_landmarks:
|
||||||
|
# get landmarks, suppose only one face is detected
|
||||||
face_landmarks = self.results.multi_face_landmarks[0]
|
face_landmarks = self.results.multi_face_landmarks[0]
|
||||||
|
|
||||||
|
# convert landmarks to numpy array
|
||||||
landmarks = np.array([(lm.x, lm.y, lm.z) for lm in face_landmarks.landmark])
|
landmarks = np.array([(lm.x, lm.y, lm.z) for lm in face_landmarks.landmark])
|
||||||
landmarks = landmarks.T
|
landmarks = landmarks.T
|
||||||
|
|
||||||
|
# remove refined landmarks
|
||||||
if self.refine_landmarks:
|
if self.refine_landmarks:
|
||||||
landmarks = landmarks[:, :468]
|
landmarks = landmarks[:, :UNREFINED_LANDMARKS]
|
||||||
|
|
||||||
metric_landmarks, pose_transform_mat = get_metric_landmarks(landmarks.copy(), self.pcf)
|
# get pose from landmarks
|
||||||
|
metric_landmarks, pose_transform_mat = get_metric_landmarks(landmarks, self.pcf)
|
||||||
|
|
||||||
self.model_points = metric_landmarks[0:3, points_idx].T
|
# extract rotation and translation vectors
|
||||||
|
|
||||||
# see here:
|
|
||||||
# https://github.com/google/mediapipe/issues/1379#issuecomment-752534379
|
|
||||||
pose_transform_mat[1:3, :] = -pose_transform_mat[1:3, :]
|
pose_transform_mat[1:3, :] = -pose_transform_mat[1:3, :]
|
||||||
self.mp_rotation_vector, _ = cv2.Rodrigues(pose_transform_mat[:3, :3])
|
self.mp_rotation_vector, _ = cv2.Rodrigues(pose_transform_mat[:3, :3])
|
||||||
self.mp_translation_vector = pose_transform_mat[:3, 3, None]
|
self.mp_translation_vector = pose_transform_mat[:3, 3, None]
|
||||||
|
|
||||||
self.pose_transform_mat = pose_transform_mat
|
# define axis
|
||||||
|
self.center = metric_landmarks[:, NOSE_LANDMARK].T
|
||||||
|
self.x = np.array([7, 0, 0])
|
||||||
|
self.y = np.array([0, 7, 0])
|
||||||
|
self.z = np.array([0, 0, 7])
|
||||||
|
|
||||||
def draw_axis(self) -> None:
|
def draw_axis(self) -> None:
|
||||||
"""Draw the face axis on the frame."""
|
"""Draw the face axis on the frame."""
|
||||||
nose_tip = self.model_points[0]
|
# project axis
|
||||||
self.x = self.model_points[0] + [7, 0, 0]
|
(nose_pointers, _) = cv2.projectPoints(
|
||||||
self.y = self.model_points[0] + [0, 7, 0]
|
np.array([np.zeros(3), self.x, self.y, self.z]) + self.center,
|
||||||
self.z = self.model_points[0] + [0, 0, 7]
|
|
||||||
|
|
||||||
(nose_pointer2D, _) = cv2.projectPoints(
|
|
||||||
np.array([nose_tip, self.x, self.y, self.z]),
|
|
||||||
self.mp_rotation_vector,
|
self.mp_rotation_vector,
|
||||||
self.mp_translation_vector,
|
self.mp_translation_vector,
|
||||||
self.camera_matrix,
|
self.camera_matrix,
|
||||||
self.dist_coeff,
|
self.dist_coeff,
|
||||||
)
|
)
|
||||||
|
|
||||||
nose_tip_2D, nose_tip_2D_x, nose_tip_2D_y, nose_tip_2D_z = nose_pointer2D.squeeze().astype(int)
|
# extract projected vectors
|
||||||
|
nose_tip_2D, nose_tip_2D_x, nose_tip_2D_y, nose_tip_2D_z = nose_pointers.squeeze().astype(int)
|
||||||
|
|
||||||
|
# draw axis
|
||||||
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_x, (0, 0, 255), 2)
|
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_x, (0, 0, 255), 2)
|
||||||
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_y, (0, 255, 0), 2)
|
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_y, (0, 255, 0), 2)
|
||||||
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_z, (255, 0, 0), 2)
|
cv2.line(self.frame, nose_tip_2D, nose_tip_2D_z, (255, 0, 0), 2)
|
||||||
|
@ -205,16 +231,6 @@ class Environment:
|
||||||
landmark_drawing_spec=self.mp_drawing_styles.DrawingSpec((0, 0, 0), 0, 0),
|
landmark_drawing_spec=self.mp_drawing_styles.DrawingSpec((0, 0, 0), 0, 0),
|
||||||
)
|
)
|
||||||
|
|
||||||
# draw subset of landmarks
|
|
||||||
landmark_subset = landmark_pb2.NormalizedLandmarkList(
|
|
||||||
landmark=[face_landmarks.landmark[i] for i in points_idx]
|
|
||||||
)
|
|
||||||
self.mp_drawing.draw_landmarks(
|
|
||||||
self.frame,
|
|
||||||
landmark_subset,
|
|
||||||
landmark_drawing_spec=self.mp_drawing_styles.DrawingSpec((0, 0, 255), 2, 0),
|
|
||||||
)
|
|
||||||
|
|
||||||
def draw_avatar(self) -> None:
|
def draw_avatar(self) -> None:
|
||||||
"""Draw the avatar on the screen."""
|
"""Draw the avatar on the screen."""
|
||||||
# clear avatar frame
|
# clear avatar frame
|
||||||
|
|
32
src/utils.py
32
src/utils.py
|
@ -1,32 +0,0 @@
|
||||||
import numpy as np
|
|
||||||
from mediapipe.python.solutions.drawing_utils import _normalized_to_pixel_coordinates
|
|
||||||
|
|
||||||
# def landmark2vec(landmark, screen):
|
|
||||||
# """Convert a landmark to a pygame Vector2."""
|
|
||||||
# return pg.Vector2(
|
|
||||||
# _normalized_to_pixel_coordinates(
|
|
||||||
# np.clip(landmark.x, 0, 1),
|
|
||||||
# np.clip(landmark.y, 0, 1),
|
|
||||||
# screen.get_width(),
|
|
||||||
# screen.get_height(),
|
|
||||||
# ) # type: ignore
|
|
||||||
# )
|
|
||||||
|
|
||||||
|
|
||||||
def landmark2vec(landmark) -> np.ndarray:
|
|
||||||
"""Convert a landmark to numpy array."""
|
|
||||||
return np.clip(
|
|
||||||
[
|
|
||||||
landmark.x,
|
|
||||||
landmark.y,
|
|
||||||
landmark.z,
|
|
||||||
],
|
|
||||||
a_min=0,
|
|
||||||
a_max=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
LANDMARKS_LEFT_SIDE = [109, 67, 103, 54, 21, 162, 127, 234, 93, 132, 58, 172, 136, 150, 149, 176, 148]
|
|
||||||
LANDMARKS_RIGHT_SIDE = [338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377]
|
|
||||||
LANDMARKS_BOTTOM_SIDE = [93, 132, 152, 361, 323]
|
|
||||||
LANDMARKS_TOP_SIDE = [127, 162, 10, 389, 356]
|
|
Loading…
Reference in a new issue