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 | 99 ------------------------------------------------- 1 files changed, 1 insertions(+), 98 deletions(-) diff --git a/code/datasets.py b/code/datasets.py index c7fc7f7..b2b9ca3 100644 --- a/code/datasets.py +++ b/code/datasets.py @@ -128,7 +128,7 @@ yaw = pose[1] * 180 / np.pi roll = pose[2] * 180 / np.pi - ds = np.random.randint(1,11) + 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) @@ -159,88 +159,6 @@ 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_SR(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) - - # 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 - - rnd = np.random.random_sample() - if rnd < 0.5: - ds = 10 - 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() - 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) - - img_ycc = img.convert('YCbCr') - - # Bin values - bins = np.array(range(-99, 102, 3)) - binned_pose = np.digitize([yaw, pitch, roll], bins) - 1 - - labels = torch.LongTensor(np.concatenate((binned_pose, shape), axis = 0)) - cont_labels = torch.FloatTensor([yaw, pitch, roll]) - - # Transforms - img = transforms.Scale(240)(img) - img = transforms.RandomCrop(224)(img) - img_ycc = img.convert('YCbCr') - img = transforms.ToTensor() - img_ycc = transforms.ToTensor() - - return img, img_ycc, labels, cont_labels, self.X_train[index] def __len__(self): # 122,450 @@ -395,21 +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)) -- Gitblit v1.8.0