improve style text infer process (#2055)
* improve style text * fix dead loop
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littletomatodonkey
GitHub
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6a42745f96
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@ -38,7 +38,15 @@ class StyleTextRecPredictor(object):
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self.std = config["Predictor"]["std"]
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self.expand_result = config["Predictor"]["expand_result"]
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def predict(self, style_input, text_input):
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def reshape_to_same_height(self, img_list):
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h = img_list[0].shape[0]
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for idx in range(1, len(img_list)):
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new_w = round(1.0 * img_list[idx].shape[1] /
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img_list[idx].shape[0] * h)
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img_list[idx] = cv2.resize(img_list[idx], (new_w, h))
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return img_list
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def predict_single_image(self, style_input, text_input):
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style_input = self.rep_style_input(style_input, text_input)
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tensor_style_input = self.preprocess(style_input)
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tensor_text_input = self.preprocess(text_input)
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@ -64,6 +72,21 @@ class StyleTextRecPredictor(object):
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"fake_bg": fake_bg,
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}
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def predict(self, style_input, text_input_list):
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if not isinstance(text_input_list, (tuple, list)):
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return self.predict_single_image(style_input, text_input_list)
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synth_result_list = []
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for text_input in text_input_list:
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synth_result = self.predict_single_image(style_input, text_input)
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synth_result_list.append(synth_result)
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for key in synth_result:
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res = [r[key] for r in synth_result_list]
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res = self.reshape_to_same_height(res)
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synth_result[key] = np.concatenate(res, axis=1)
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return synth_result
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def preprocess(self, img):
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img = (img.astype('float32') * self.scale - self.mean) / self.std
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img_height, img_width, channel = img.shape
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@ -12,6 +12,8 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import numpy as np
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import cv2
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from utils.config import ArgsParser, load_config, override_config
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from utils.logging import get_logger
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@ -36,8 +38,9 @@ class ImageSynthesiser(object):
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self.predictor = getattr(predictors, predictor_method)(self.config)
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def synth_image(self, corpus, style_input, language="en"):
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corpus, text_input = self.text_drawer.draw_text(corpus, language)
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synth_result = self.predictor.predict(style_input, text_input)
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corpus_list, text_input_list = self.text_drawer.draw_text(
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corpus, language, style_input_width=style_input.shape[1])
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synth_result = self.predictor.predict(style_input, text_input_list)
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return synth_result
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@ -59,12 +62,15 @@ class DatasetSynthesiser(ImageSynthesiser):
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for i in range(self.output_num):
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style_data = self.style_sampler.sample()
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style_input = style_data["image"]
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corpus_language, text_input_label = self.corpus_generator.generate(
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)
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text_input_label, text_input = self.text_drawer.draw_text(
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text_input_label, corpus_language)
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corpus_language, text_input_label = self.corpus_generator.generate()
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text_input_label_list, text_input_list = self.text_drawer.draw_text(
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text_input_label,
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corpus_language,
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style_input_width=style_input.shape[1])
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synth_result = self.predictor.predict(style_input, text_input)
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text_input_label = "".join(text_input_label_list)
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synth_result = self.predictor.predict(style_input, text_input_list)
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fake_fusion = synth_result["fake_fusion"]
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self.writer.save_image(fake_fusion, text_input_label)
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self.writer.save_label()
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@ -1,5 +1,6 @@
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from PIL import Image, ImageDraw, ImageFont
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import numpy as np
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import cv2
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from utils.logging import get_logger
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@ -28,7 +29,11 @@ class StdTextDrawer(object):
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else:
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return int((self.height - 4)**2 / font_height)
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def draw_text(self, corpus, language="en", crop=True):
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def draw_text(self,
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corpus,
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language="en",
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crop=True,
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style_input_width=None):
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if language not in self.support_languages:
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self.logger.warning(
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"language {} not supported, use en instead.".format(language))
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@ -37,21 +42,43 @@ class StdTextDrawer(object):
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width = min(self.max_width, len(corpus) * self.height) + 4
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else:
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width = len(corpus) * self.height + 4
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if style_input_width is not None:
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width = min(width, style_input_width)
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corpus_list = []
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text_input_list = []
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while len(corpus) != 0:
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bg = Image.new("RGB", (width, self.height), color=(127, 127, 127))
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draw = ImageDraw.Draw(bg)
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char_x = 2
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font = self.font_dict[language]
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for i, char_i in enumerate(corpus):
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i = 0
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while i < len(corpus):
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char_i = corpus[i]
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char_size = font.getsize(char_i)[0]
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draw.text((char_x, 2), char_i, fill=(0, 0, 0), font=font)
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char_x += char_size
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if char_x >= width:
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corpus = corpus[0:i + 1]
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self.logger.warning("corpus length exceed limit: {}".format(
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corpus))
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break
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# split when char_x exceeds char size and index is not 0 (at least 1 char should be wroten on the image)
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if char_x + char_size >= width and i != 0:
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text_input = np.array(bg).astype(np.uint8)
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text_input = text_input[:, 0:char_x, :]
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return corpus, text_input
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corpus_list.append(corpus[0:i])
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text_input_list.append(text_input)
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corpus = corpus[i:]
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break
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draw.text((char_x, 2), char_i, fill=(0, 0, 0), font=font)
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char_x += char_size
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i += 1
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# the whole text is shorter than style input
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if i == len(corpus):
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text_input = np.array(bg).astype(np.uint8)
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text_input = text_input[:, 0:char_x, :]
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corpus_list.append(corpus[0:i])
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text_input_list.append(text_input)
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corpus = corpus[i:]
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break
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return corpus_list, text_input_list
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