mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-06-26 22:19:57 +00:00
refactor: no need to inherit in python3 clean the code (#5659)
### What problem does this PR solve? As title ### Type of change - [x] Refactoring Signed-off-by: yihong0618 <zouzou0208@gmail.com>
This commit is contained in:
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a64f4539e7
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4326873af6
@ -224,7 +224,7 @@ class TenantLLMService(CommonService):
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return list(objs)
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return list(objs)
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class LLMBundle(object):
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class LLMBundle:
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def __init__(self, tenant_id, llm_type, llm_name=None, lang="Chinese"):
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def __init__(self, tenant_id, llm_type, llm_name=None, lang="Chinese"):
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self.tenant_id = tenant_id
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self.tenant_id = tenant_id
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self.llm_type = llm_type
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self.llm_type = llm_type
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@ -1170,7 +1170,7 @@ class RAGFlowPdfParser:
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return poss
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return poss
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class PlainParser(object):
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class PlainParser:
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def __call__(self, filename, from_page=0, to_page=100000, **kwargs):
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def __call__(self, filename, from_page=0, to_page=100000, **kwargs):
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self.outlines = []
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self.outlines = []
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lines = []
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lines = []
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@ -19,7 +19,7 @@ from io import BytesIO
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from pptx import Presentation
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from pptx import Presentation
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class RAGFlowPptParser(object):
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class RAGFlowPptParser:
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def __init__(self):
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def __init__(self):
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super().__init__()
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super().__init__()
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@ -122,7 +122,7 @@ def load_model(model_dir, nm):
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return loaded_model
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return loaded_model
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class TextRecognizer(object):
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class TextRecognizer:
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def __init__(self, model_dir):
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def __init__(self, model_dir):
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self.rec_image_shape = [int(v) for v in "3, 48, 320".split(",")]
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self.rec_image_shape = [int(v) for v in "3, 48, 320".split(",")]
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self.rec_batch_num = 16
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self.rec_batch_num = 16
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@ -393,7 +393,7 @@ class TextRecognizer(object):
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return rec_res, time.time() - st
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return rec_res, time.time() - st
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class TextDetector(object):
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class TextDetector:
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def __init__(self, model_dir):
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def __init__(self, model_dir):
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pre_process_list = [{
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pre_process_list = [{
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'DetResizeForTest': {
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'DetResizeForTest': {
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@ -506,7 +506,7 @@ class TextDetector(object):
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return dt_boxes, time.time() - st
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return dt_boxes, time.time() - st
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class OCR(object):
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class OCR:
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def __init__(self, model_dir=None):
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def __init__(self, model_dir=None):
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"""
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"""
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If you have trouble downloading HuggingFace models, -_^ this might help!!
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If you have trouble downloading HuggingFace models, -_^ this might help!!
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@ -23,7 +23,7 @@ import math
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from PIL import Image
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from PIL import Image
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class DecodeImage(object):
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class DecodeImage:
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""" decode image """
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""" decode image """
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def __init__(self,
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def __init__(self,
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@ -65,7 +65,7 @@ class DecodeImage(object):
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return data
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return data
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class StandardizeImage(object):
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class StandardizeImag:
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"""normalize image
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"""normalize image
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Args:
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Args:
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mean (list): im - mean
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mean (list): im - mean
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@ -102,7 +102,7 @@ class StandardizeImage(object):
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return im, im_info
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return im, im_info
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class NormalizeImage(object):
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class NormalizeImage:
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""" normalize image such as subtract mean, divide std
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""" normalize image such as subtract mean, divide std
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"""
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"""
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@ -129,7 +129,7 @@ class NormalizeImage(object):
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return data
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return data
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class ToCHWImage(object):
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class ToCHWImage:
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""" convert hwc image to chw image
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""" convert hwc image to chw image
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"""
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"""
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@ -145,7 +145,7 @@ class ToCHWImage(object):
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return data
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return data
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class KeepKeys(object):
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class KeepKeys:
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def __init__(self, keep_keys, **kwargs):
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def __init__(self, keep_keys, **kwargs):
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self.keep_keys = keep_keys
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self.keep_keys = keep_keys
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@ -156,7 +156,7 @@ class KeepKeys(object):
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return data_list
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return data_list
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class Pad(object):
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class Pad:
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def __init__(self, size=None, size_div=32, **kwargs):
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def __init__(self, size=None, size_div=32, **kwargs):
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if size is not None and not isinstance(size, (int, list, tuple)):
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if size is not None and not isinstance(size, (int, list, tuple)):
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raise TypeError("Type of target_size is invalid. Now is {}".format(
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raise TypeError("Type of target_size is invalid. Now is {}".format(
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@ -194,7 +194,7 @@ class Pad(object):
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return data
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return data
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class LinearResize(object):
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class LinearResize:
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"""resize image by target_size and max_size
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"""resize image by target_size and max_size
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Args:
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Args:
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target_size (int): the target size of image
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target_size (int): the target size of image
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@ -261,7 +261,7 @@ class LinearResize(object):
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return im_scale_y, im_scale_x
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return im_scale_y, im_scale_x
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class Resize(object):
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class Resize:
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def __init__(self, size=(640, 640), **kwargs):
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def __init__(self, size=(640, 640), **kwargs):
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self.size = size
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self.size = size
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@ -291,7 +291,7 @@ class Resize(object):
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return data
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return data
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class DetResizeForTest(object):
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class DetResizeForTest:
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def __init__(self, **kwargs):
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def __init__(self, **kwargs):
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super(DetResizeForTest, self).__init__()
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super(DetResizeForTest, self).__init__()
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self.resize_type = 0
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self.resize_type = 0
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@ -421,7 +421,7 @@ class DetResizeForTest(object):
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return img, [ratio_h, ratio_w]
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return img, [ratio_h, ratio_w]
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class E2EResizeForTest(object):
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class E2EResizeForTest:
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def __init__(self, **kwargs):
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def __init__(self, **kwargs):
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super(E2EResizeForTest, self).__init__()
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super(E2EResizeForTest, self).__init__()
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self.max_side_len = kwargs['max_side_len']
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self.max_side_len = kwargs['max_side_len']
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@ -489,7 +489,7 @@ class E2EResizeForTest(object):
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return im, (ratio_h, ratio_w)
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return im, (ratio_h, ratio_w)
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class KieResize(object):
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class KieResize:
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def __init__(self, **kwargs):
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def __init__(self, **kwargs):
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super(KieResize, self).__init__()
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super(KieResize, self).__init__()
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self.max_side, self.min_side = kwargs['img_scale'][0], kwargs[
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self.max_side, self.min_side = kwargs['img_scale'][0], kwargs[
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@ -539,7 +539,7 @@ class KieResize(object):
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return points
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return points
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class SRResize(object):
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class SRResize:
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def __init__(self,
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def __init__(self,
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imgH=32,
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imgH=32,
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imgW=128,
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imgW=128,
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@ -576,7 +576,7 @@ class SRResize(object):
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return data
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return data
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class ResizeNormalize(object):
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class ResizeNormalize:
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def __init__(self, size, interpolation=Image.BICUBIC):
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def __init__(self, size, interpolation=Image.BICUBIC):
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self.size = size
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self.size = size
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self.interpolation = interpolation
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self.interpolation = interpolation
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@ -588,7 +588,7 @@ class ResizeNormalize(object):
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return img_numpy
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return img_numpy
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class GrayImageChannelFormat(object):
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class GrayImageChannelFormat:
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"""
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"""
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format gray scale image's channel: (3,h,w) -> (1,h,w)
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format gray scale image's channel: (3,h,w) -> (1,h,w)
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Args:
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Args:
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@ -612,7 +612,7 @@ class GrayImageChannelFormat(object):
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return data
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return data
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class Permute(object):
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class Permute:
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"""permute image
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"""permute image
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Args:
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Args:
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to_bgr (bool): whether convert RGB to BGR
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to_bgr (bool): whether convert RGB to BGR
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@ -635,7 +635,7 @@ class Permute(object):
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return im, im_info
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return im, im_info
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class PadStride(object):
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class PadStride:
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""" padding image for model with FPN, instead PadBatch(pad_to_stride) in original config
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""" padding image for model with FPN, instead PadBatch(pad_to_stride) in original config
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Args:
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Args:
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stride (bool): model with FPN need image shape % stride == 0
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stride (bool): model with FPN need image shape % stride == 0
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@ -38,7 +38,7 @@ def build_post_process(config, global_config=None):
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return module_class(**config)
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return module_class(**config)
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class DBPostProcess(object):
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class DBPostProcess:
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"""
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"""
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The post process for Differentiable Binarization (DB).
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The post process for Differentiable Binarization (DB).
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"""
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"""
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@ -259,7 +259,7 @@ class DBPostProcess(object):
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return boxes_batch
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return boxes_batch
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class BaseRecLabelDecode(object):
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class BaseRecLabelDecode:
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""" Convert between text-label and text-index """
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""" Convert between text-label and text-index """
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def __init__(self, character_dict_path=None, use_space_char=False):
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def __init__(self, character_dict_path=None, use_space_char=False):
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@ -28,7 +28,7 @@ from .operators import preprocess
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from . import operators
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from . import operators
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from .ocr import load_model
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from .ocr import load_model
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class Recognizer(object):
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class Recognizer:
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def __init__(self, label_list, task_name, model_dir=None):
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def __init__(self, label_list, task_name, model_dir=None):
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"""
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"""
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If you have trouble downloading HuggingFace models, -_^ this might help!!
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If you have trouble downloading HuggingFace models, -_^ this might help!!
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@ -24,7 +24,7 @@ from azure.storage.blob import ContainerClient
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@singleton
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@singleton
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class RAGFlowAzureSasBlob(object):
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class RAGFlowAzureSasBlob:
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def __init__(self):
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def __init__(self):
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self.conn = None
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self.conn = None
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self.container_url = os.getenv('CONTAINER_URL', settings.AZURE["container_url"])
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self.container_url = os.getenv('CONTAINER_URL', settings.AZURE["container_url"])
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@ -24,7 +24,7 @@ from azure.storage.filedatalake import FileSystemClient
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@singleton
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@singleton
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class RAGFlowAzureSpnBlob(object):
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class RAGFlowAzureSpnBlob:
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def __init__(self):
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def __init__(self):
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self.conn = None
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self.conn = None
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self.account_url = os.getenv('ACCOUNT_URL', settings.AZURE["account_url"])
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self.account_url = os.getenv('ACCOUNT_URL', settings.AZURE["account_url"])
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@ -24,7 +24,7 @@ from rag.utils import singleton
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@singleton
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@singleton
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class RAGFlowMinio(object):
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class RAGFlowMinio:
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def __init__(self):
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def __init__(self):
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self.conn = None
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self.conn = None
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self.__open__()
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self.__open__()
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@ -24,7 +24,7 @@ from rag import settings
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@singleton
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@singleton
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class RAGFlowOSS(object):
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class RAGFlowOSS:
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def __init__(self):
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def __init__(self):
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self.conn = None
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self.conn = None
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self.oss_config = settings.OSS
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self.oss_config = settings.OSS
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@ -23,7 +23,7 @@ from rag.utils import singleton
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from rag import settings
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from rag import settings
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@singleton
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@singleton
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class RAGFlowS3(object):
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class RAGFlowS3:
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def __init__(self):
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def __init__(self):
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self.conn = None
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self.conn = None
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self.s3_config = settings.S3
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self.s3_config = settings.S3
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@ -14,7 +14,7 @@
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# limitations under the License.
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# limitations under the License.
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#
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#
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class Base(object):
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class Base:
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def __init__(self, rag, res_dict):
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def __init__(self, rag, res_dict):
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self.rag = rag
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self.rag = rag
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for k, v in res_dict.items():
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for k, v in res_dict.items():
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