utils.py

import cv2
import numpy as np


def get_affine_transform(center, scale, output_size, rot=0., inv=False):
    if not isinstance(scale, np.ndarray) and not isinstance(scale, list) and not isinstance(scale, tuple):
        scale = np.array([scale, scale], dtype=np.float32)

    if not isinstance(output_size, np.ndarray) and not isinstance(output_size, list) and not isinstance(output_size, tuple):
        output_size = np.array([output_size, output_size], dtype=np.float32)

    scale_tmp = scale
    src_w = scale_tmp[0]
    src_h = scale_tmp[1]
    dst_w = output_size[0]
    dst_h = output_size[1]

    rot_rad = np.pi * rot / 180
    src_dir = get_dir([0, src_h * -0.5], rot_rad)
    dst_dir = np.array([0, dst_h * -0.5], np.float32)

    src = np.zeros((3, 2), dtype=np.float32)
    dst = np.zeros((3, 2), dtype=np.float32)
    src[0, :] = center
    src[1, :] = center + src_dir
    dst[0, :] = [dst_w * 0.5, dst_h * 0.5]
    dst[1, :] = np.array([dst_w * 0.5, dst_h * 0.5], np.float32) + dst_dir
    src[2:, :] = get_3rd_point(src[0, :], src[1, :])
    dst[2:, :] = get_3rd_point(dst[0, :], dst[1, :])

    if inv:
        trans = cv2.getAffineTransform(np.float32(dst), np.float32(src))
    else:
        trans = cv2.getAffineTransform(np.float32(src), np.float32(dst))

    return trans


def affine_transform(pt, t):
    new_pt = np.array([pt[0], pt[1], 1.], dtype=np.float32).T
    new_pt = np.dot(t, new_pt)
    return new_pt[:2]


def get_3rd_point(a, b):
    direct = a - b
    return b + np.array([-direct[1], direct[0]], dtype=np.float32)


def get_dir(src_point, rot_rad):
    sn, cs = np.sin(rot_rad), np.cos(rot_rad)

    src_result = [0, 0]
    src_result[0] = src_point[0] * cs - src_point[1] * sn
    src_result[1] = src_point[0] * sn + src_point[1] * cs

    return src_result


def preprocess_image(image, c, s, tgt_w, tgt_h):
    trans_input = get_affine_transform(c, s, (tgt_w, tgt_h))
    image = cv2.warpAffine(image, trans_input, (tgt_w, tgt_h), flags=cv2.INTER_LINEAR)
    image = image.astype(np.float32)

    image[..., 0] -= 103.939
    image[..., 1] -= 116.779
    image[..., 2] -= 123.68

    return image