Python translate_beam_searchの例

コード例 #1

    def batch_predict(self, images):
        """
        param: images : list of ndarray

        """
        batch = self.batch_process(images)
        batch = batch.to(self.config['device'])
        if self.config['predictor']['beamsearch']:
            sent = translate_beam_search(batch, self.model)
            s = sent
        else:
            sents = translate(batch, self.model).tolist()

        sequences = self.vocab.batch_decode(sents)
        return sequences

コード例 #2

ファイル: predictor.py プロジェクト: tienthienhd/vietocr

    def predict(self, img):
        img = process_input(img, self.config['dataset']['image_height'],
                            self.config['dataset']['image_min_width'],
                            self.config['dataset']['image_max_width'])
        img = img.to(self.config['device'])

        if self.config['predictor']['beamsearch']:
            sent = translate_beam_search(img, self.model)
            s = sent
        else:
            s = translate(img, self.model)[0].tolist()

        s = self.vocab.decode(s)

        return s

コード例 #3

    def predict(self, img):
        img = self.preprocess_input(img)
        img = np.expand_dims(img, axis=0)
        img = torch.FloatTensor(img)
        img = img.to(self.config['device'])

        if self.config['predictor']['beamsearch']:
            sent = translate_beam_search(img, self.model)
            s = sent
        else:
            s = translate(img, self.model)[0].tolist()

        s = self.vocab.decode(s)

        return s

コード例 #4

    def predict(self, img, return_prob=False):
        img = process_input(img, self.config['dataset']['image_height'],
                            self.config['dataset']['image_min_width'],
                            self.config['dataset']['image_max_width'])
        img = img.to(self.config['device'])

        if self.config['predictor']['beamsearch']:
            sent = translate_beam_search(img, self.model)
            s = sent
            prob = None
        else:
            s, prob = translate(img, self.model)
            s = s[0].tolist()
            prob = prob[0]

        s = self.vocab.decode(s)

        if return_prob:
            return s, prob
        else:
            return s

コード例 #5

ファイル: reader.py プロジェクト: mjnk9xw/IDCardVNRecognition

    def predict(self, img, return_prob=False):
        img = self.preprocess_input(img)
        img = np.expand_dims(img, axis=0)
        img = torch.FloatTensor(img)
        img = img.to(self.config['device'])

        if self.config['predictor']['beamsearch']:
            sent = translate_beam_search(img, self.model)
            s = sent
            prob = None
        else:
            s, prob = translate(img, self.model)
            s = s[0].tolist()
            prob = prob[0]

        s = self.vocab.decode(s)

        if return_prob:
            return s, prob
        else:
            return s