Loss of accuracy in recognizing when exporting a trained model

Markitosik commented 9 months ago

System Environment: Windows 11, Python 3.9.9

Version: Paddle 2.7+ PaddleOCR

I trained a recognition model using the configuration file config.yml and obtained excellent results on my dataset. However, after exporting the model for inference, the accuracy significantly decreases. Command code: python PaddleOCR/tools/export_model.py -c config.yml -o Global.pretrained_model="output/rec/mark/best_accuracy" Global.save_inference_dir=./mark Configuration file: Global: use_gpu: true epoch_num: 250 log_smooth_window: 20 print_batch_step: 10 save_model_dir: ./output/rec/mark1/ save_epoch_step: 3

eval_batch_step: [0, 2000] cal_metric_during_train: True pretrained_model: checkpoints: save_inference_dir: ./mark use_visualdl: TRue infer_img: doc/imgs_words_en/word_10.png

character_dict_path: ../Practice1/ppocr/utils/dict1.txt character_type: EN max_text_length: 25 infer_mode: True use_space_char: False save_res_path: ./output/rec/dict1_0.txt

Optimizer: name: Adam beta1: 0.9 beta2: 0.999 lr: learning_rate: 0.0005 regularizer: name: 'L2' factor: 0

Architecture: model_type: rec algorithm: CRNN Transform: Backbone: name: MobileNetV3 scale: 0.5 model_name: large Neck: name: SequenceEncoder encoder_type: rnn hidden_size: 96 Head: name: CTCHead fc_decay: 0

Loss: name: CTCLoss

PostProcess: name: CTCLabelDecode

Metric: name: RecMetric main_indicator: acc

Train: dataset: name: SimpleDataSet data_dir: ../Practice1/dataset/train/images/ label_file_list: ['../Practice1/dataset/train/train_annotation.txt'] transforms:

DecodeImage: # load image img_mode: BGR channel_first: False
CTCLabelEncode: # Class handling label
RecResizeImg: image_shape: [3, 32, 100]
KeepKeys: keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order loader: shuffle: True batch_size_per_card: 256 drop_last: True num_workers: 8 use_shared_memory: False

Eval: dataset: name: SimpleDataSet data_dir: ../Practice1/dataset/val/images/ label_file_list: ['../Practice1/dataset/val/val_annotation.txt'] transforms:

DecodeImage: # load image img_mode: BGR channel_first: False
CTCLabelEncode: # Class handling label
RecResizeImg: image_shape: [3, 32, 100]
KeepKeys: keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order loader: shuffle: False drop_last: False batch_size_per_card: 256 num_workers: 4 use_shared_memory: False

What am I doing wrong?

tink2123 commented 9 months ago

What command did you use to predict? It is recommended that you use this command：

python tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 32, 100" --rec_char_dict_path="../Practice1/ppocr/utils/dict1.txt"

Markitosik commented 9 months ago

An error occurs when executing this command

(venv) PS C:\Studies\Practice> python PaddleOCR/tools/infer/predict_rec.py --image_dir="C:\Users\Mark\Downloads\dataset2\oi_9988.jpg" --rec_model_dir="C:\Studies\Practice\mark2.0" --rec_image_shape="3, 32, 100" --rec_char_dict_path="../Practice1/ppocr/utils/dict1.txt"

[2024/01/30 22:27:02] ppocr INFO: In PP-OCRv3, rec_image_shape parameter defaults to '3, 48, 320', if you are using recognition model with PP-OCRv2 or an older version, please set --rec_image_shape='3,32,320 [2024/01/30 22:27:02] ppocr INFO: Traceback (most recent call last): File "C:\Studies\Practice\PaddleOCR\tools\infer\predict_rec.py", line 662, in main recres, = text_recognizer(img_list) File "C:\Studies\Practice\PaddleOCR\tools\infer\predict_rec.py", line 628, in call rec_result = self.postprocess_op(preds) File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 121, in call text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True) File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 83, in decode char_list = [ File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 84, in self.character[text_id] IndexError: list index out of range

[2024/01/30 22:27:02] ppocr INFO: list index out of range

What could be the reason for this?

Markitosik commented 9 months ago

I have achieved ~98% accuracy during training. I want to use my trained model in code, for example, instead of typing the command in the terminal every time. from paddleocr import PaddleOCR,draw_ocr ocr = PaddleOCR(rec_model_dir='{your_rec_model_dir}', rec_char_dict_path='{your_rec_char_dict_path}') img_path = 'img_12.jpg' result = ocr.ocr(img_path)

But when using this code and the final output model based on my trained model on the dataset where I previously performed validation, I am getting only 5% accuracy.

Why does it happen like this?

tink2123 commented 9 months ago

An error occurs when executing this command

(venv) PS C:\Studies\Practice> python PaddleOCR/tools/infer/predict_rec.py --image_dir="C:\Users\Mark\Downloads\dataset2\oi_9988.jpg" --rec_model_dir="C:\Studies\Practice\mark2.0" --rec_image_shape="3, 32, 100" --rec_char_dict_path="../Practice1/ppocr/utils/dict1.txt"

[2024/01/30 22:27:02] ppocr INFO: In PP-OCRv3, rec_image_shape parameter defaults to '3, 48, 320', if you are using recognition model with PP-OCRv2 or an older version, please set --rec_image_shape='3,32,320 [2024/01/30 22:27:02] ppocr INFO: Traceback (most recent call last): File "C:\Studies\Practice\PaddleOCR\tools\infer\predict_rec.py", line 662, in main recres, = text_recognizer(img_list) File "C:\Studies\Practice\PaddleOCR\tools\infer\predict_rec.py", line 628, in call rec_result = self.postprocess_op(preds) File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 121, in call text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True) File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 83, in decode char_list = [ File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py", line 84, in self.character[text_id] IndexError: list index out of range

[2024/01/30 22:27:02] ppocr INFO: list index out of range

What could be the reason for this?

Please confirm whether the dictionary used in the training and exported configuration file is ../Practice1/ppocr/utils/dict1.txt. It needs to be consistent.

tink2123 commented 9 months ago

I have achieved ~98% accuracy during training. I want to use my trained model in code, for example, instead of typing the command in the terminal every time. from paddleocr import PaddleOCR,draw_ocr ocr = PaddleOCR(rec_model_dir='{your_rec_model_dir}', rec_char_dict_path='{your_rec_char_dict_path}') img_path = 'img_12.jpg' result = ocr.ocr(img_path)

But when using this code and the final output model based on my trained model on the dataset where I previously performed validation, I am getting only 5% accuracy.

Why does it happen like this?

As you said, you achieved 98% accuracy on the text recognition evaluation set, and you also need to select a single text recognition prediction in order to align the behavior when making predictions.

from paddleocr import PaddleOCR

ocr = PaddleOCR()  # need to run only once to download and load model into memory
img_path = 'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result = ocr.ocr(img_path, det=False)
for idx in range(len(result)):
    res = result[idx]
    for line in res:
        print(line)

Refer to the introduction in the documentation：https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/doc/doc_en/whl_en.md

Markitosik commented 9 months ago

Yes, I use a dictionary located at this path (../Practice1/ppocr/utils/dict1.txt) throughout the entire model training

tink2123 commented 9 months ago

Yes, I use a dictionary located at this path (../Practice1/ppocr/utils/dict1.txt) throughout the entire model training

maybe you could print text_id and len(self.character) in File "C:\Studies\Practice\PaddleOCR\ppocr\postprocess\rec_postprocess.py" Line84, to find the reason of IndexError.

Markitosik commented 9 months ago

python PaddleOCR/tools/infer/predict_rec.py --image_dir="C:\Users\Mark\Downloads\dataset2\oi_9988.jpg" --rec_model_dir="C:\Studies \Practice\mark2.0" --rec_image_shape="3, 32, 100" --rec_char_dict_path="../Practice1/ppocr/utils/dict1.txt"

I was able to figure out how to run the above command and it gives the correct answer, but there is a problem. Why am I getting different results on the file when using the same model? When I use the command, I get the correct answer. But when I use the model in the program, it gives me the wrong answer. Command:

python /tools/infer/predict_rec.py --image_dir="id_1000_value_176_881.jpg" --rec_model_dir="/mark1.4" --rec_image_shape="3, 32, 100" --rec_char_dict_path="/ppocr/utils/dict1.txt"

Code:

from paddleocr import PaddleOCR

ocr = PaddleOCR(use_gpu=True, rec_model_dir='/mark1.4',
                rec_char_dict_path='ppocr/utils/dict1.txt')

result = ocr.ocr('id_1000_value_176_881.jpg', cls=False, det=False)
answer = str(result[0][0][0])
print(answer)

tink2123 commented 9 months ago

All parameters need to be consistent, try code:

from paddleocr import PaddleOCR

ocr = PaddleOCR(use_gpu=True, rec_model_dir='/mark1.4', rec_image_shape="3, 32, 100",
                rec_char_dict_path='ppocr/utils/dict1.txt')

result = ocr.ocr('id_1000_value_176_881.jpg', cls=False, det=False)
answer = str(result[0][0][0])
print(answer)

Markitosik commented 9 months ago

Even when using my output model in this code, nothing changes in the results.

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Loss of accuracy in recognizing when exporting a trained model #11551