From 97a3af3bbf12925d421782236a749cfe4f1a4ef9 Mon Sep 17 00:00:00 2001 From: tink2123 Date: Mon, 6 Jul 2020 13:53:12 +0800 Subject: [PATCH] add distort and space --- configs/rec/rec_chinese_lite_train.yml | 1 + configs/rec/rec_icdar15_train.yml | 1 + ppocr/data/rec/dataset_traversal.py | 18 +- ppocr/data/rec/img_tools.py | 252 ++++++++++++++++++++++++- ppocr/utils/ppocr_keys_v1.txt | 3 +- 5 files changed, 269 insertions(+), 6 deletions(-) diff --git a/configs/rec/rec_chinese_lite_train.yml b/configs/rec/rec_chinese_lite_train.yml index b64313a1..3368876d 100755 --- a/configs/rec/rec_chinese_lite_train.yml +++ b/configs/rec/rec_chinese_lite_train.yml @@ -14,6 +14,7 @@ Global: character_type: ch character_dict_path: ./ppocr/utils/ppocr_keys_v1.txt loss_type: ctc + distort: true reader_yml: ./configs/rec/rec_chinese_reader.yml pretrain_weights: checkpoints: diff --git a/configs/rec/rec_icdar15_train.yml b/configs/rec/rec_icdar15_train.yml index 8aa96160..d0b75628 100755 --- a/configs/rec/rec_icdar15_train.yml +++ b/configs/rec/rec_icdar15_train.yml @@ -13,6 +13,7 @@ Global: max_text_length: 25 character_type: en loss_type: ctc + distort: true reader_yml: ./configs/rec/rec_icdar15_reader.yml pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy checkpoints: diff --git a/ppocr/data/rec/dataset_traversal.py b/ppocr/data/rec/dataset_traversal.py index e57717d9..23852db6 100755 --- a/ppocr/data/rec/dataset_traversal.py +++ b/ppocr/data/rec/dataset_traversal.py @@ -45,6 +45,8 @@ class LMDBReader(object): self.use_tps = False if "tps" in params: self.ues_tps = True + if "distort" in params: + self.use_distort = params['distort'] if params['mode'] == 'train': self.batch_size = params['train_batch_size_per_card'] self.drop_last = True @@ -142,7 +144,8 @@ class LMDBReader(object): label=label, char_ops=self.char_ops, loss_type=self.loss_type, - max_text_length=self.max_text_length) + max_text_length=self.max_text_length, + distort=self.use_distort) if outs is None: continue yield outs @@ -185,6 +188,8 @@ class SimpleReader(object): self.use_tps = False if "tps" in params: self.use_tps = True + if "distort" in params: + self.use_distort = params['distort'] if params['mode'] == 'train': self.batch_size = params['train_batch_size_per_card'] self.drop_last = True @@ -232,9 +237,14 @@ class SimpleReader(object): img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) label = substr[1] - outs = process_image(img, self.image_shape, label, - self.char_ops, self.loss_type, - self.max_text_length) + outs = process_image( + img=img, + image_shape=self.image_shape, + label=label, + char_ops=self.char_ops, + loss_type=self.loss_type, + max_text_length=self.max_text_length, + distort=self.use_distort) if outs is None: continue yield outs diff --git a/ppocr/data/rec/img_tools.py b/ppocr/data/rec/img_tools.py index 9c4bfa4d..cc891156 100755 --- a/ppocr/data/rec/img_tools.py +++ b/ppocr/data/rec/img_tools.py @@ -15,6 +15,7 @@ import math import cv2 import numpy as np +import random from ppocr.utils.utility import initial_logger logger = initial_logger() @@ -89,6 +90,252 @@ def get_img_data(value): return imgori +def flag(): + """ + flag + """ + return 1 if random.random() > 0.5000001 else -1 + + +def cvtColor(img): + """ + cvtColor + """ + hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) + delta = 0.001 * random.random() * flag() + hsv[:, :, 2] = hsv[:, :, 2] * (1 + delta) + new_img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) + return new_img + + +def blur(img): + """ + blur + """ + h, w, _ = img.shape + if h > 10 and w > 10: + return cv2.GaussianBlur(img, (5, 5), 1) + else: + return img + + +def doudong(img): + """ + doudong + """ + w, h, _ = img.shape + if h > 10 and w > 10: + thres = min(w, h) + s = int(random.random() * thres * 0.01) + src_img = img.copy() + for i in range(s): + img[i:, i:, :] = src_img[:w - i, :h - i, :] + return img + else: + return img + + +def add_gasuss_noise(image, mean=0, var=0.1): + + noise = np.random.normal(mean, var**0.5, image.shape) + out = image + 0.5 * noise + out = np.clip(out, 0, 255) + out = np.uint8(out) + return out + + +def get_crop(image): + """ + random crop + """ + h, w, _ = image.shape + top_min = 1 + top_max = 8 + top_crop = int(random.randint(top_min, top_max)) + + crop_img = image.copy() + + ratio = random.randint(0, 1) + if ratio: + crop_img = crop_img[top_crop:h, :, :] + else: + crop_img = crop_img[0:h - top_crop, :, :] + return crop_img + + +class Config: + """ + Config + """ + + def __init__(self, ): + self.anglex = random.random() * 30 + self.angley = random.random() * 15 + self.anglez = random.random() * 10 + self.fov = 42 + self.r = 0 + self.shearx = random.random() * 0.3 + self.sheary = random.random() * 0.05 + self.borderMode = cv2.BORDER_REPLICATE + + def make(self, w, h, ang): + """ + make + """ + self.anglex = random.random() * 5 * flag() + self.angley = random.random() * 5 * flag() + self.anglez = -1 * random.random() * int(ang) * flag() + self.fov = 42 + self.r = 0 + self.shearx = 0 + self.sheary = 0 + self.borderMode = cv2.BORDER_REPLICATE + self.w = w + self.h = h + + self.perspective = True + self.crop = True + self.affine = False + self.reverse = True + self.noise = True + self.dou = False + self.blur = True + self.color = True + + +def rad(x): + """ + rad + """ + return x * np.pi / 180 + + +def get_warpR(config): + """ + get_warpR + """ + anglex, angley, anglez, fov, w, h, r = \ + config.anglex, config.angley, config.anglez, config.fov, config.w, config.h, config.r + if w > 69 and w < 112: + anglex = anglex * 1.5 + + z = np.sqrt(w**2 + h**2) / 2 / np.tan(rad(fov / 2)) + # Homogeneous coordinate transformation matrix + rx = np.array([[1, 0, 0, 0], + [0, np.cos(rad(anglex)), -np.sin(rad(anglex)), 0], [ + 0, + -np.sin(rad(anglex)), + np.cos(rad(anglex)), + 0, + ], [0, 0, 0, 1]], np.float32) + ry = np.array([[np.cos(rad(angley)), 0, np.sin(rad(angley)), 0], + [0, 1, 0, 0], [ + -np.sin(rad(angley)), + 0, + np.cos(rad(angley)), + 0, + ], [0, 0, 0, 1]], np.float32) + rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0, 0], + [-np.sin(rad(anglez)), np.cos(rad(anglez)), 0, 0], + [0, 0, 1, 0], [0, 0, 0, 1]], np.float32) + r = rx.dot(ry).dot(rz) + # generate 4 points + pcenter = np.array([h / 2, w / 2, 0, 0], np.float32) + p1 = np.array([0, 0, 0, 0], np.float32) - pcenter + p2 = np.array([w, 0, 0, 0], np.float32) - pcenter + p3 = np.array([0, h, 0, 0], np.float32) - pcenter + p4 = np.array([w, h, 0, 0], np.float32) - pcenter + dst1 = r.dot(p1) + dst2 = r.dot(p2) + dst3 = r.dot(p3) + dst4 = r.dot(p4) + list_dst = [dst1, dst2, dst3, dst4] + org = np.array([[0, 0], [w, 0], [0, h], [w, h]], np.float32) + dst = np.zeros((4, 2), np.float32) + # Project onto the image plane + for i in range(4): + dst[i, 0] = list_dst[i][0] * z / (z - list_dst[i][2]) + pcenter[0] + dst[i, 1] = list_dst[i][1] * z / (z - list_dst[i][2]) + pcenter[1] + warpR = cv2.getPerspectiveTransform(org, dst) + + dst1, dst2, dst3, dst4 = dst + r1 = int(min(dst1[1], dst2[1])) + r2 = int(max(dst3[1], dst4[1])) + c1 = int(min(dst1[0], dst3[0])) + c2 = int(max(dst2[0], dst4[0])) + + try: + ratio = min(1.0 * h / (r2 - r1), 1.0 * w / (c2 - c1)) + + dx = -c1 + dy = -r1 + T1 = np.float32([[1., 0, dx], [0, 1., dy], [0, 0, 1.0 / ratio]]) + ret = T1.dot(warpR) + except: + ratio = 1.0 + T1 = np.float32([[1., 0, 0], [0, 1., 0], [0, 0, 1.]]) + ret = T1 + return ret, (-r1, -c1), ratio, dst + + +def get_warpAffine(config): + """ + get_warpAffine + """ + anglez = config.anglez + rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0], + [-np.sin(rad(anglez)), np.cos(rad(anglez)), 0]], np.float32) + return rz + + +def warp(img, ang): + """ + warp + """ + h, w, _ = img.shape + config = Config() + config.make(w, h, ang) + new_img = img + + if config.perspective: + tp = random.randint(1, 100) + if tp >= 50: + warpR, (r1, c1), ratio, dst = get_warpR(config) + new_w = int(np.max(dst[:, 0])) - int(np.min(dst[:, 0])) + new_img = cv2.warpPerspective( + new_img, + warpR, (int(new_w * ratio), h), + borderMode=config.borderMode) + if config.crop: + img_height, img_width = img.shape[0:2] + tp = random.randint(1, 100) + if tp >= 50 and img_height >= 20 and img_width >= 20: + new_img = get_crop(new_img) + if config.affine: + warpT = get_warpAffine(config) + new_img = cv2.warpAffine( + new_img, warpT, (w, h), borderMode=config.borderMode) + if config.blur: + tp = random.randint(1, 100) + if tp >= 50: + new_img = blur(new_img) + if config.color: + tp = random.randint(1, 100) + if tp >= 50: + new_img = cvtColor(new_img) + if config.dou: + new_img = doudong(new_img) + if config.noise: + tp = random.randint(1, 100) + if tp >= 50: + new_img = add_gasuss_noise(new_img) + if config.reverse: + tp = random.randint(1, 100) + if tp >= 50: + new_img = 255 - new_img + return new_img + + def process_image(img, image_shape, label=None, @@ -96,7 +343,10 @@ def process_image(img, loss_type=None, max_text_length=None, tps=None, - infer_mode=False): + infer_mode=False, + distort=False): + if distort: + img = warp(img, 10) if infer_mode and char_ops.character_type == "ch" and not tps: norm_img = resize_norm_img_chinese(img, image_shape) else: diff --git a/ppocr/utils/ppocr_keys_v1.txt b/ppocr/utils/ppocr_keys_v1.txt index 84b885d8..3ca70d0a 100644 --- a/ppocr/utils/ppocr_keys_v1.txt +++ b/ppocr/utils/ppocr_keys_v1.txt @@ -6620,4 +6620,5 @@ j 緖 續 紹 -懮 \ No newline at end of file +懮 + -- GitLab