From b730bbd6ea565d7689964661c53a6074654b5d3b Mon Sep 17 00:00:00 2001 From: natanielruiz <nataniel777@hotmail.com> Date: 星期一, 30 十月 2017 05:30:52 +0800 Subject: [PATCH] next --- code/datasets.py | 106 +++++++++++++++++++++++++++++++++++++++++++---------- 1 files changed, 86 insertions(+), 20 deletions(-) diff --git a/code/datasets.py b/code/datasets.py index 17f1899..b2b9ca3 100644 --- a/code/datasets.py +++ b/code/datasets.py @@ -6,6 +6,7 @@ from PIL import Image, ImageFilter import utils +from torchvision import transforms def stack_grayscale_tensor(tensor): tensor = torch.cat([tensor, tensor, tensor], 0) @@ -53,6 +54,84 @@ pitch = pose[0] * 180 / np.pi yaw = pose[1] * 180 / np.pi roll = pose[2] * 180 / np.pi + + # Flip? + rnd = np.random.random_sample() + if rnd < 0.5: + yaw = -yaw + roll = -roll + img = img.transpose(Image.FLIP_LEFT_RIGHT) + + # Blur? + rnd = np.random.random_sample() + if rnd < 0.05: + img = img.filter(ImageFilter.BLUR) + + # Bin values + bins = np.array(range(-99, 102, 3)) + binned_pose = np.digitize([yaw, pitch, roll], bins) - 1 + + # Get shape + shape = np.load(shape_path) + + labels = torch.LongTensor(np.concatenate((binned_pose, shape), axis = 0)) + cont_labels = torch.FloatTensor([yaw, pitch, roll]) + + if self.transform is not None: + img = self.transform(img) + + return img, labels, cont_labels, self.X_train[index] + + def __len__(self): + # 122,450 + return self.length + +class Pose_300W_LP_random_ds(Dataset): + def __init__(self, data_dir, filename_path, transform, img_ext='.jpg', annot_ext='.mat', image_mode='RGB'): + self.data_dir = data_dir + self.transform = transform + self.img_ext = img_ext + self.annot_ext = annot_ext + + filename_list = get_list_from_filenames(filename_path) + + self.X_train = filename_list + self.y_train = filename_list + self.image_mode = image_mode + self.length = len(filename_list) + + def __getitem__(self, index): + img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext)) + img = img.convert(self.image_mode) + mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext) + shape_path = os.path.join(self.data_dir, self.y_train[index] + '_shape.npy') + + # Crop the face + pt2d = utils.get_pt2d_from_mat(mat_path) + x_min = min(pt2d[0,:]) + y_min = min(pt2d[1,:]) + x_max = max(pt2d[0,:]) + y_max = max(pt2d[1,:]) + + # k = 0.2 to 0.40 + k = np.random.random_sample() * 0.2 + 0.2 + x_min -= 0.6 * k * abs(x_max - x_min) + y_min -= 2 * k * abs(y_max - y_min) + x_max += 0.6 * k * abs(x_max - x_min) + y_max += 0.6 * k * abs(y_max - y_min) + img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max))) + + # We get the pose in radians + pose = utils.get_ypr_from_mat(mat_path) + # And convert to degrees. + pitch = pose[0] * 180 / np.pi + yaw = pose[1] * 180 / np.pi + roll = pose[2] * 180 / np.pi + + ds = 1 + np.random.randint(0,4) * 5 + original_size = img.size + img = img.resize((img.size[0] / ds, img.size[1] / ds), resample=Image.NEAREST) + img = img.resize((original_size[0], original_size[1]), resample=Image.NEAREST) # Flip? rnd = np.random.random_sample() @@ -172,10 +251,10 @@ y_max += 0.6 * k * abs(y_max - y_min) img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max))) - ds = 5 + ds = 3 original_size = img.size - img = img.resize((img.size[0] / ds, img.size[1] / ds), resample=0) - img = img.resize((original_size[0], original_size[1]), resample=0) + img = img.resize((img.size[0] / ds, img.size[1] / ds), resample=Image.NEAREST) + img = img.resize((original_size[0], original_size[1]), resample=Image.NEAREST) # We get the pose in radians pose = utils.get_ypr_from_mat(mat_path) @@ -234,21 +313,6 @@ yaw = -yaw roll = -roll img = img.transpose(Image.FLIP_LEFT_RIGHT) - - # Blur? - # rnd = np.random.random_sample() - # if rnd < 0.05: - # img = img.filter(ImageFilter.BLUR) - # if rnd < 0.025: - # img = img.filter(ImageFilter.BLUR) - # - # rnd = np.random.random_sample() - # if rnd < 0.05: - # nb = np.random.randint(1,5) - # img = img.rotate(-nb) - # elif rnd > 0.95: - # nb = np.random.randint(1,5) - # img = img.rotate(nb) # Bin values bins = np.array(range(-99, 102, 3)) @@ -412,9 +476,11 @@ R = R[:3,:] pose_annot.close() + R = np.transpose(R) + roll = -np.arctan2(R[1][0], R[0][0]) * 180 / np.pi - yaw = np.arctan2(-R[2][0], np.sqrt(R[2][1] ** 2 + R[2][2] ** 2)) * 180 / np.pi - pitch = -np.arctan2(R[2][1], R[2][2]) * 180 / np.pi + yaw = -np.arctan2(-R[2][0], np.sqrt(R[2][1] ** 2 + R[2][2] ** 2)) * 180 / np.pi + pitch = np.arctan2(R[2][1], R[2][2]) * 180 / np.pi # Loosely crop face k = 0.35 -- Gitblit v1.8.0