### What problem does this PR solve? As title ### Type of change - [x] Refactoring Signed-off-by: yihong0618 <zouzou0208@gmail.com>tags/v0.17.1
| @@ -224,7 +224,7 @@ class TenantLLMService(CommonService): | |||
| return list(objs) | |||
| class LLMBundle(object): | |||
| class LLMBundle: | |||
| def __init__(self, tenant_id, llm_type, llm_name=None, lang="Chinese"): | |||
| self.tenant_id = tenant_id | |||
| self.llm_type = llm_type | |||
| @@ -1170,7 +1170,7 @@ class RAGFlowPdfParser: | |||
| return poss | |||
| class PlainParser(object): | |||
| class PlainParser: | |||
| def __call__(self, filename, from_page=0, to_page=100000, **kwargs): | |||
| self.outlines = [] | |||
| lines = [] | |||
| @@ -19,7 +19,7 @@ from io import BytesIO | |||
| from pptx import Presentation | |||
| class RAGFlowPptParser(object): | |||
| class RAGFlowPptParser: | |||
| def __init__(self): | |||
| super().__init__() | |||
| @@ -122,7 +122,7 @@ def load_model(model_dir, nm): | |||
| return loaded_model | |||
| class TextRecognizer(object): | |||
| class TextRecognizer: | |||
| def __init__(self, model_dir): | |||
| self.rec_image_shape = [int(v) for v in "3, 48, 320".split(",")] | |||
| self.rec_batch_num = 16 | |||
| @@ -393,7 +393,7 @@ class TextRecognizer(object): | |||
| return rec_res, time.time() - st | |||
| class TextDetector(object): | |||
| class TextDetector: | |||
| def __init__(self, model_dir): | |||
| pre_process_list = [{ | |||
| 'DetResizeForTest': { | |||
| @@ -506,7 +506,7 @@ class TextDetector(object): | |||
| return dt_boxes, time.time() - st | |||
| class OCR(object): | |||
| class OCR: | |||
| def __init__(self, model_dir=None): | |||
| """ | |||
| If you have trouble downloading HuggingFace models, -_^ this might help!! | |||
| @@ -23,7 +23,7 @@ import math | |||
| from PIL import Image | |||
| class DecodeImage(object): | |||
| class DecodeImage: | |||
| """ decode image """ | |||
| def __init__(self, | |||
| @@ -65,7 +65,7 @@ class DecodeImage(object): | |||
| return data | |||
| class StandardizeImage(object): | |||
| class StandardizeImag: | |||
| """normalize image | |||
| Args: | |||
| mean (list): im - mean | |||
| @@ -102,7 +102,7 @@ class StandardizeImage(object): | |||
| return im, im_info | |||
| class NormalizeImage(object): | |||
| class NormalizeImage: | |||
| """ normalize image such as subtract mean, divide std | |||
| """ | |||
| @@ -129,7 +129,7 @@ class NormalizeImage(object): | |||
| return data | |||
| class ToCHWImage(object): | |||
| class ToCHWImage: | |||
| """ convert hwc image to chw image | |||
| """ | |||
| @@ -145,7 +145,7 @@ class ToCHWImage(object): | |||
| return data | |||
| class KeepKeys(object): | |||
| class KeepKeys: | |||
| def __init__(self, keep_keys, **kwargs): | |||
| self.keep_keys = keep_keys | |||
| @@ -156,7 +156,7 @@ class KeepKeys(object): | |||
| return data_list | |||
| class Pad(object): | |||
| class Pad: | |||
| def __init__(self, size=None, size_div=32, **kwargs): | |||
| if size is not None and not isinstance(size, (int, list, tuple)): | |||
| raise TypeError("Type of target_size is invalid. Now is {}".format( | |||
| @@ -194,7 +194,7 @@ class Pad(object): | |||
| return data | |||
| class LinearResize(object): | |||
| class LinearResize: | |||
| """resize image by target_size and max_size | |||
| Args: | |||
| target_size (int): the target size of image | |||
| @@ -261,7 +261,7 @@ class LinearResize(object): | |||
| return im_scale_y, im_scale_x | |||
| class Resize(object): | |||
| class Resize: | |||
| def __init__(self, size=(640, 640), **kwargs): | |||
| self.size = size | |||
| @@ -291,7 +291,7 @@ class Resize(object): | |||
| return data | |||
| class DetResizeForTest(object): | |||
| class DetResizeForTest: | |||
| def __init__(self, **kwargs): | |||
| super(DetResizeForTest, self).__init__() | |||
| self.resize_type = 0 | |||
| @@ -421,7 +421,7 @@ class DetResizeForTest(object): | |||
| return img, [ratio_h, ratio_w] | |||
| class E2EResizeForTest(object): | |||
| class E2EResizeForTest: | |||
| def __init__(self, **kwargs): | |||
| super(E2EResizeForTest, self).__init__() | |||
| self.max_side_len = kwargs['max_side_len'] | |||
| @@ -489,7 +489,7 @@ class E2EResizeForTest(object): | |||
| return im, (ratio_h, ratio_w) | |||
| class KieResize(object): | |||
| class KieResize: | |||
| def __init__(self, **kwargs): | |||
| super(KieResize, self).__init__() | |||
| self.max_side, self.min_side = kwargs['img_scale'][0], kwargs[ | |||
| @@ -539,7 +539,7 @@ class KieResize(object): | |||
| return points | |||
| class SRResize(object): | |||
| class SRResize: | |||
| def __init__(self, | |||
| imgH=32, | |||
| imgW=128, | |||
| @@ -576,7 +576,7 @@ class SRResize(object): | |||
| return data | |||
| class ResizeNormalize(object): | |||
| class ResizeNormalize: | |||
| def __init__(self, size, interpolation=Image.BICUBIC): | |||
| self.size = size | |||
| self.interpolation = interpolation | |||
| @@ -588,7 +588,7 @@ class ResizeNormalize(object): | |||
| return img_numpy | |||
| class GrayImageChannelFormat(object): | |||
| class GrayImageChannelFormat: | |||
| """ | |||
| format gray scale image's channel: (3,h,w) -> (1,h,w) | |||
| Args: | |||
| @@ -612,7 +612,7 @@ class GrayImageChannelFormat(object): | |||
| return data | |||
| class Permute(object): | |||
| class Permute: | |||
| """permute image | |||
| Args: | |||
| to_bgr (bool): whether convert RGB to BGR | |||
| @@ -635,7 +635,7 @@ class Permute(object): | |||
| return im, im_info | |||
| class PadStride(object): | |||
| class PadStride: | |||
| """ padding image for model with FPN, instead PadBatch(pad_to_stride) in original config | |||
| Args: | |||
| stride (bool): model with FPN need image shape % stride == 0 | |||
| @@ -38,7 +38,7 @@ def build_post_process(config, global_config=None): | |||
| return module_class(**config) | |||
| class DBPostProcess(object): | |||
| class DBPostProcess: | |||
| """ | |||
| The post process for Differentiable Binarization (DB). | |||
| """ | |||
| @@ -259,7 +259,7 @@ class DBPostProcess(object): | |||
| return boxes_batch | |||
| class BaseRecLabelDecode(object): | |||
| class BaseRecLabelDecode: | |||
| """ Convert between text-label and text-index """ | |||
| def __init__(self, character_dict_path=None, use_space_char=False): | |||
| @@ -28,7 +28,7 @@ from .operators import preprocess | |||
| from . import operators | |||
| from .ocr import load_model | |||
| class Recognizer(object): | |||
| class Recognizer: | |||
| def __init__(self, label_list, task_name, model_dir=None): | |||
| """ | |||
| If you have trouble downloading HuggingFace models, -_^ this might help!! | |||
| @@ -24,7 +24,7 @@ from azure.storage.blob import ContainerClient | |||
| @singleton | |||
| class RAGFlowAzureSasBlob(object): | |||
| class RAGFlowAzureSasBlob: | |||
| def __init__(self): | |||
| self.conn = None | |||
| self.container_url = os.getenv('CONTAINER_URL', settings.AZURE["container_url"]) | |||
| @@ -24,7 +24,7 @@ from azure.storage.filedatalake import FileSystemClient | |||
| @singleton | |||
| class RAGFlowAzureSpnBlob(object): | |||
| class RAGFlowAzureSpnBlob: | |||
| def __init__(self): | |||
| self.conn = None | |||
| self.account_url = os.getenv('ACCOUNT_URL', settings.AZURE["account_url"]) | |||
| @@ -24,7 +24,7 @@ from rag.utils import singleton | |||
| @singleton | |||
| class RAGFlowMinio(object): | |||
| class RAGFlowMinio: | |||
| def __init__(self): | |||
| self.conn = None | |||
| self.__open__() | |||
| @@ -24,7 +24,7 @@ from rag import settings | |||
| @singleton | |||
| class RAGFlowOSS(object): | |||
| class RAGFlowOSS: | |||
| def __init__(self): | |||
| self.conn = None | |||
| self.oss_config = settings.OSS | |||
| @@ -23,7 +23,7 @@ from rag.utils import singleton | |||
| from rag import settings | |||
| @singleton | |||
| class RAGFlowS3(object): | |||
| class RAGFlowS3: | |||
| def __init__(self): | |||
| self.conn = None | |||
| self.s3_config = settings.S3 | |||
| @@ -14,7 +14,7 @@ | |||
| # limitations under the License. | |||
| # | |||
| class Base(object): | |||
| class Base: | |||
| def __init__(self, rag, res_dict): | |||
| self.rag = rag | |||
| for k, v in res_dict.items(): | |||