Commit 8e70591b authored by narugo1992's avatar narugo1992
Browse files

dev(narugo): add benchmark for detectiomn

parent 70a1a3ce

docs/source/api_doc/ocr/ocr_demo.plot.py

+5 −7
Original line number Diff line number Diff line
@@ -4,13 +4,11 @@ from imgutils.detect.visual import detection_visualize 
from imgutils.ocr import ocr

from plot import image_plot



_max_size = 480





def _detect(img, **kwargs):

def _detect(img, *, max_size=None, **kwargs):

    img = load_image(img, mode='RGB', force_background='white')

    if min(img.height, img.width) > _max_size:

        r = _max_size / min(img.height, img.width)

    if max_size is not None and min(img.height, img.width) > max_size:

        r = max_size / min(img.height, img.width)

        img = img.resize((

            int(round(img.width * r)),

            int(round(img.height * r)),
@@ -21,10 +19,10 @@ def _detect(img, **kwargs): 


if __name__ == '__main__':

    image_plot(

        (_detect('post_text.jpg', recognize_model='japan_PP-OCRv3_rec'), 'Text of Post'),

        (_detect('post_text.jpg', recognize_model='japan_PP-OCRv3_rec', max_size=480), 'Text of Post'),

        (_detect('anime_subtitle.jpg'), 'Subtitle of Anime'),

        (_detect('comic.jpg'), 'Comic'),

        (_detect('plot.png'), 'Complex'),

        columns=2,

        figsize=(12, 9),

        figsize=(13, 7.5),

    )

docs/source/api_doc/ocr/ocr_demo.plot.py.svg

deleted100644 → 0
+0 −539

File deleted.

Preview size limit exceeded, changes collapsed.

docs/source/api_doc/ocr/ocr_det_benchmark.plot.py

0 → 100644
+34 −0
Original line number Diff line number Diff line 
import random



from benchmark import BaseBenchmark, create_plot_cli

from imgutils.ocr.detect import _detect_text, _list_det_models





class OCRDetectBenchmark(BaseBenchmark):

    def __init__(self, model):

        BaseBenchmark.__init__(self)

        self.model = model



    def load(self):

        from imgutils.ocr.detect import _open_ocr_detection_model

        _ = _open_ocr_detection_model(self.model)



    def unload(self):

        from imgutils.ocr.detect import _open_ocr_detection_model

        _open_ocr_detection_model.cache_clear()



    def run(self):

        image_file = random.choice(self.all_images)

        _ = _detect_text(image_file, model=self.model)





if __name__ == '__main__':

    create_plot_cli(

        [

            (model, OCRDetectBenchmark(model))

            for model in _list_det_models()

        ],

        title='Benchmark for OCR Detections',

        run_times=10,

        try_times=20,

    )()

imgutils/ocr/detect.py

+2 −2
Original line number Diff line number Diff line
@@ -123,7 +123,7 @@ def _normalize(data, mean=(0.48145466, 0.4578275, 0.40821073), std=(0.26862954, 
_ALIGN = 64





def _get_text_points(image: ImageTyping, model: str = 'ch_PP-OCRv4_det_infer',

def _get_text_points(image: ImageTyping, model: str = 'ch_PP-OCRv4_det',

                     heat_threshold: float = 0.3, box_threshold: float = 0.7,

                     max_candidates: int = 1000, unclip_ratio: float = 2.0):

    origin_width, origin_height = width, height = image.size
@@ -154,7 +154,7 @@ def _get_text_points(image: ImageTyping, model: str = 'ch_PP-OCRv4_det_infer', 
    return retval





def _detect_text(image: ImageTyping, model: str = 'ch_PP-OCRv4_det_infer',

def _detect_text(image: ImageTyping, model: str = 'ch_PP-OCRv4_det',

                 heat_threshold: float = 0.3, box_threshold: float = 0.7,

                 max_candidates: int = 1000, unclip_ratio: float = 2.0):

    image = load_image(image, force_background='white', mode='RGB')

imgutils/ocr/recognize.py

+1 −1
Original line number Diff line number Diff line
@@ -59,7 +59,7 @@ def decode(text_index, model: str, text_prob=None, is_remove_duplicate=False): 
    return retval





def _text_recognize(image: ImageTyping, model: str = 'ch_PP-OCRv4_det_infer',

def _text_recognize(image: ImageTyping, model: str = 'ch_PP-OCRv4_rec',

                    is_remove_duplicate: bool = False) -> Tuple[str, float]:

    image = load_image(image, force_background='white', mode='RGB')

    r = 48 / image.height