repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
graphiti | tests/embedder/test_openai.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 127 | 4,396 |
graphiti | tests/embedder/embedder_fixtures.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 21 | 777 |
graphiti | tests/embedder/test_gemini.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 396 | 15,091 |
graphiti | tests/driver/test_falkordb_ops_routing.py | .py | """Unit tests for FalkorDB per-group-id query routing in the operations layer.
These cover the *namespace/ops* read path (e.g. ``graphiti.nodes.episode.
get_by_group_ids``), which delegates to the Falkor ``*Operations`` classes with
the base driver (pointed at ``default_db``). FalkorDB stores each ``group_id`` in
its ... | 120 | 4,473 |
graphiti | tests/driver/test_falkordb_driver.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 432 | 17,532 |
graphiti | tests/llm_client/test_openai_generic_client.py | .py | import json
from types import SimpleNamespace
import openai
import pytest
from pydantic import BaseModel
from graphiti_core.llm_client.config import LLMConfig
from graphiti_core.llm_client.errors import EmptyResponseError, RateLimitError
from graphiti_core.llm_client.openai_generic_client import OpenAIGenericClient
f... | 171 | 6,369 |
graphiti | tests/llm_client/test_anthropic_client.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 256 | 9,893 |
graphiti | tests/llm_client/test_client.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 109 | 4,484 |
graphiti | tests/llm_client/test_errors.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 77 | 2,764 |
graphiti | tests/llm_client/test_azure_openai_client.py | .py | from types import SimpleNamespace
import pytest
from pydantic import BaseModel
from graphiti_core.llm_client.azure_openai_client import AzureOpenAILLMClient
from graphiti_core.llm_client.config import LLMConfig
class DummyResponses:
def __init__(self):
self.parse_calls: list[dict] = []
async def pa... | 127 | 3,639 |
graphiti | tests/llm_client/test_openai_client.py | .py | from types import SimpleNamespace
import pytest
from pydantic import BaseModel
from graphiti_core.llm_client.config import LLMConfig
from graphiti_core.llm_client.openai_base_client import DEFAULT_MODEL, DEFAULT_REASONING
from graphiti_core.llm_client.openai_client import OpenAIClient
class DummyResponses:
def ... | 222 | 6,849 |
graphiti | tests/llm_client/test_gemini_client.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 483 | 20,920 |
graphiti | tests/llm_client/test_token_tracker.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 215 | 7,553 |
graphiti | tests/llm_client/test_anthropic_client_int.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 86 | 2,872 |
graphiti | tests/llm_client/test_cache.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 113 | 4,036 |
graphiti | tests/utils/test_content_chunking.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 781 | 30,429 |
graphiti | tests/utils/test_concatenate_episodes.py | .py | """Tests for graphiti_core.utils.text_utils."""
from datetime import datetime, timezone
from unittest.mock import MagicMock
from graphiti_core.utils.text_utils import concatenate_episodes
def _make_episode(content: str, valid_at: datetime | None = None) -> MagicMock:
ep = MagicMock()
ep.content = content
... | 53 | 2,201 |
graphiti | tests/utils/maintenance/test_bulk_utils.py | .py | from collections import deque
from unittest.mock import AsyncMock, MagicMock
import pytest
from graphiti_core.edges import EntityEdge
from graphiti_core.graphiti_types import GraphitiClients
from graphiti_core.nodes import EntityNode, EpisodeType, EpisodicNode
from graphiti_core.utils import bulk_utils
from graphiti_... | 566 | 17,819 |
graphiti | tests/utils/maintenance/test_attribute_utils.py | .py | import logging
import pytest
from pydantic import BaseModel, Field
from graphiti_core.utils.maintenance.attribute_utils import (
DEFAULT_ATTRIBUTE_MAX_LENGTH,
LIST_TOTAL_LENGTH_MULTIPLIER,
apply_capped_attributes,
cap_string_attributes,
)
class _Person(BaseModel):
phones: str | None = Field(
... | 257 | 9,927 |
graphiti | tests/utils/maintenance/test_node_operations.py | .py | import logging
from collections import defaultdict
from unittest.mock import AsyncMock, MagicMock
import pytest
from graphiti_core.graphiti_types import GraphitiClients
from graphiti_core.nodes import EntityNode, EpisodeType, EpisodicNode
from graphiti_core.utils.datetime_utils import utc_now
from graphiti_core.utils... | 921 | 30,945 |
graphiti | tests/utils/maintenance/test_edge_operations.py | .py | from datetime import datetime, timedelta, timezone
from types import SimpleNamespace
from unittest.mock import AsyncMock, MagicMock
import pytest
from pydantic import BaseModel
from graphiti_core.edges import EntityEdge
from graphiti_core.nodes import EntityNode, EpisodicNode
from graphiti_core.search.search_config i... | 774 | 24,523 |
graphiti | tests/utils/maintenance/test_entity_extraction.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 662 | 21,832 |
graphiti | tests/utils/maintenance/test_remove_communities.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 99 | 3,191 |
graphiti | tests/utils/search/test_edge_cross_encoder_rrf_shortlist.py | .py | from datetime import datetime, timezone
from types import SimpleNamespace
import pytest
from graphiti_core.edges import EntityEdge
from graphiti_core.search.search import edge_search
from graphiti_core.search.search_config import EdgeReranker, EdgeSearchConfig, EdgeSearchMethod
from graphiti_core.search.search_filter... | 124 | 4,509 |
graphiti | tests/utils/search/test_search_tracing.py | .py | from collections.abc import Generator
from contextlib import contextmanager
from types import SimpleNamespace
import pytest
from graphiti_core.search.search import edge_search, search
from graphiti_core.search.search_config import EdgeSearchConfig, EdgeSearchMethod, SearchConfig
from graphiti_core.search.search_filte... | 150 | 4,674 |
graphiti | tests/utils/search/search_utils_test.py | .py | from unittest.mock import AsyncMock, patch
import pytest
from graphiti_core.nodes import EntityNode
from graphiti_core.search.search_filters import SearchFilters
from graphiti_core.search.search_utils import hybrid_node_search
@pytest.mark.asyncio
async def test_hybrid_node_search_deduplication():
# Mock the da... | 164 | 6,567 |
graphiti | tests/utils/search/test_search_security.py | .py | from types import SimpleNamespace
from unittest.mock import MagicMock
import pytest
from pydantic import ValidationError
from graphiti_core.driver.driver import GraphProvider
from graphiti_core.driver.falkordb.operations.search_ops import _build_falkor_fulltext_query
from graphiti_core.driver.neo4j.operations.search_... | 161 | 6,459 |
graphiti | tests/utils/search/test_edge_bfs_query_shape.py | .py | """Query-shape regression tests for edge_bfs_search (no live database).
Completes #1500 on the generic path in ``graphiti_core/search/search_utils.py``,
which is what executes today for FalkorDB and Neo4j (``driver.search_interface``
is never assigned, so the driver-level operations modules patched by #1500 are
not re... | 137 | 4,784 |
graphiti | tests/cross_encoder/test_bge_reranker_client_int.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 79 | 2,403 |
graphiti | tests/cross_encoder/test_gemini_reranker_client.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 354 | 14,027 |
graphiti | tests/evals/eval_e2e_graph_building.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 181 | 6,813 |
graphiti | tests/evals/utils.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 40 | 1,184 |
graphiti | tests/evals/eval_cli.py | .py | import argparse
import asyncio
from tests.evals.eval_e2e_graph_building import build_baseline_graph, eval_graph
async def main():
parser = argparse.ArgumentParser(
description='Run eval_graph and optionally build_baseline_graph from the command line.'
)
parser.add_argument(
'--multi-sess... | 41 | 1,203 |
graphiti | examples/quickstart/quickstart_neo4j.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 240 | 9,438 |
graphiti | examples/quickstart/quickstart_neptune.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 253 | 9,774 |
graphiti | examples/quickstart/dense_vs_normal_ingestion.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 343 | 14,626 |
graphiti | examples/quickstart/quickstart_falkordb.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 257 | 10,328 |
graphiti | examples/wizard_of_oz/parser.py | .py | import os
import re
def parse_wizard_of_oz(file_path):
with open(file_path, encoding='utf-8') as file:
content = file.read()
# Split the content into chapters
chapters = re.split(r'\n\n+Chapter [IVX]+\n', content)[
1:
] # Skip the first split which is before Chapter I
episodes =... | 37 | 1,120 |
graphiti | examples/wizard_of_oz/runner.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 94 | 3,029 |
graphiti | examples/azure-openai/azure_openai_neo4j.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 226 | 8,530 |
graphiti | examples/gliner2/gliner2_neo4j.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 328 | 13,227 |
graphiti | examples/podcast/podcast_runner.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 194 | 6,988 |
graphiti | examples/podcast/transcript_parser.py | .py | import os
import re
from datetime import datetime, timedelta, timezone
from pydantic import BaseModel
class Speaker(BaseModel):
index: int
name: str
role: str
class ParsedMessage(BaseModel):
speaker_index: int
speaker_name: str
role: str
relative_timestamp: str
actual_timestamp: dat... | 125 | 4,274 |
graphiti | examples/ecommerce/runner.py | .py | """
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 124 | 4,082 |
graphiti | examples/opentelemetry/otel_stdout_example.py | .py | """
Copyright 2025, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, sof... | 126 | 4,358 |
EasyOCR | setup.py | .py | """
End-to-End Multi-Lingual Optical Character Recognition (OCR) Solution
"""
from io import open
from setuptools import setup
with open('requirements.txt', encoding="utf-8-sig") as f:
requirements = f.readlines()
def readme():
with open('README.md', encoding="utf-8-sig") as f:
README = f.read()
r... | 36 | 1,100 |
EasyOCR | trainer/utils.py | .py | import torch
import pickle
import numpy as np
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
class AttrDict(dict):
def __init__(self, *args, **kwargs):
super(AttrDict, self).__init__(*args, **kwargs)
self.__dict__ = self
##### https://github.com/githubharald/CTCDecoder/blob/... | 366 | 14,518 |
EasyOCR | trainer/train.py | .py | import os
import sys
import time
import random
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.init as init
import torch.optim as optim
import torch.utils.data
from torch.cuda.amp import autocast, GradScaler
import numpy as np
from utils import CTCLabelConverter, AttnLabelConver... | 283 | 12,198 |
EasyOCR | trainer/model.py | .py | import torch.nn as nn
from modules.transformation import TPS_SpatialTransformerNetwork
from modules.feature_extraction import VGG_FeatureExtractor, RCNN_FeatureExtractor, ResNet_FeatureExtractor
from modules.sequence_modeling import BidirectionalLSTM
from modules.prediction import Attention
class Model(nn.Module):
... | 75 | 3,573 |
EasyOCR | trainer/dataset.py | .py | import os
import sys
import re
import six
import math
import torch
import pandas as pd
from natsort import natsorted
from PIL import Image
import numpy as np
from torch.utils.data import Dataset, ConcatDataset, Subset
from torch._utils import _accumulate
import torchvision.transforms as transforms
def contrast_grey(... | 284 | 11,060 |
EasyOCR | trainer/test.py | .py | import os
import time
import string
import argparse
import torch
import torch.backends.cudnn as cudnn
import torch.utils.data
import torch.nn.functional as F
import numpy as np
from nltk.metrics.distance import edit_distance
from utils import CTCLabelConverter, AttnLabelConverter, Averager
from dataset import hierarc... | 113 | 4,722 |
EasyOCR | trainer/craft/train.py | .py | # -*- coding: utf-8 -*-
import argparse
import os
import shutil
import time
import multiprocessing as mp
import yaml
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import wandb
from config.load_config import load_yaml, DotDict
from data.dataset import SynthTextDataSet, CustomDataset... | 480 | 17,330 |
EasyOCR | trainer/craft/trainSynth.py | .py | # -*- coding: utf-8 -*-
import argparse
import os
import shutil
import time
import yaml
import multiprocessing as mp
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import wandb
from config.load_config import load_yaml, DotDict
from data.dataset import SynthTextDataSet
from loss.msel... | 410 | 14,471 |
EasyOCR | trainer/craft/eval.py | .py | # -*- coding: utf-8 -*-
import argparse
import os
import cv2
import numpy as np
import torch
import torch.backends.cudnn as cudnn
from tqdm import tqdm
import wandb
from config.load_config import load_yaml, DotDict
from model.craft import CRAFT
from metrics.eval_det_iou import DetectionIoUEvaluator
from utils.infere... | 382 | 12,008 |
EasyOCR | trainer/craft/train_distributed.py | .py | # -*- coding: utf-8 -*-
import argparse
import os
import shutil
import time
import multiprocessing as mp
import yaml
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import wandb
from config.load_config import load_yaml, DotDict
from data.dataset import SynthTextDataSet, CustomDataset... | 524 | 19,294 |
EasyOCR | trainer/craft/loss/mseloss.py | .py | import torch
import torch.nn as nn
class Loss(nn.Module):
def __init__(self):
super(Loss, self).__init__()
def forward(self, gt_region, gt_affinity, pred_region, pred_affinity, conf_map):
loss = torch.mean(
((gt_region - pred_region).pow(2) + (gt_affinity - pred_affinity).pow(2))
... | 173 | 5,709 |
EasyOCR | trainer/craft/config/load_config.py | .py | import os
import yaml
from functools import reduce
CONFIG_PATH = os.path.dirname(__file__)
def load_yaml(config_name):
with open(os.path.join(CONFIG_PATH, config_name)+ '.yaml') as file:
config = yaml.safe_load(file)
return config
class DotDict(dict):
def __getattr__(self, k):
try:
... | 37 | 987 |
EasyOCR | trainer/craft/model/vgg16_bn.py | .py | import torch
import torch.nn as nn
import torch.nn.init as init
import torchvision
from torchvision import models
from packaging import version
def init_weights(modules):
for m in modules:
if isinstance(m, nn.Conv2d):
init.xavier_uniform_(m.weight.data)
if m.bias is not None:
... | 78 | 2,962 |
EasyOCR | trainer/craft/model/craft.py | .py | """
Copyright (c) 2019-present NAVER Corp.
MIT License
"""
# -*- coding: utf-8 -*-
import torch
import torch.nn as nn
import torch.nn.functional as F
from model.vgg16_bn import vgg16_bn, init_weights
class double_conv(nn.Module):
def __init__(self, in_ch, mid_ch, out_ch):
super(double_conv, self).__ini... | 112 | 3,788 |
EasyOCR | trainer/craft/metrics/eval_det_iou.py | .py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from collections import namedtuple
import numpy as np
from shapely.geometry import Polygon
"""
cite from:
PaddleOCR, github: https://github.com/PaddlePaddle/PaddleOCR
PaddleOCR reference from :
https://github.com/MhLiao/DB/blob/3c32b808d4412680310d3d28eeb6a2d5bf1566c5/conce... | 245 | 8,665 |
EasyOCR | trainer/craft/utils/craft_utils.py | .py |
# -*- coding: utf-8 -*-
import os
import torch
import cv2
import math
import numpy as np
from data import imgproc
""" auxilary functions """
# unwarp corodinates
def warpCoord(Minv, pt):
out = np.matmul(Minv, (pt[0], pt[1], 1))
return np.array([out[0]/out[2], out[1]/out[2]])
""" end of auxilary functions ... | 345 | 14,030 |
EasyOCR | trainer/craft/utils/util.py | .py | from collections import OrderedDict
import os
import cv2
import numpy as np
from data import imgproc
from utils import craft_utils
def copyStateDict(state_dict):
if list(state_dict.keys())[0].startswith("module"):
start_idx = 1
else:
start_idx = 0
new_state_dict = OrderedDict()
for k... | 143 | 4,759 |
EasyOCR | trainer/craft/utils/inference_boxes.py | .py | import os
import re
import itertools
import cv2
import time
import numpy as np
import torch
from torch.autograd import Variable
from utils.craft_utils import getDetBoxes, adjustResultCoordinates
from data import imgproc
from data.dataset import SynthTextDataSet
import math
import xml.etree.ElementTree as elemTree
#... | 362 | 11,756 |
EasyOCR | trainer/craft/data/imgproc.py | .py | """
Copyright (c) 2019-present NAVER Corp.
MIT License
"""
# -*- coding: utf-8 -*-
import numpy as np
import cv2
from skimage import io
def loadImage(img_file):
img = io.imread(img_file) # RGB order
if img.shape[0] == 2:
img = img[0]
if len(img.shape) == 2:
img = cv2.cvtColor(img, cv2... | 92 | 2,340 |
EasyOCR | trainer/craft/data/gaussian.py | .py | import numpy as np
import cv2
from data.boxEnlarge import enlargebox
class GaussianBuilder(object):
def __init__(self, init_size, sigma, enlarge_region, enlarge_affinity):
self.init_size = init_size
self.sigma = sigma
self.enlarge_region = enlarge_region
self.enlarge_affinity = en... | 192 | 7,227 |
EasyOCR | trainer/craft/data/imgaug.py | .py | import random
import cv2
import numpy as np
from PIL import Image
from torchvision.transforms.functional import resized_crop, crop
from torchvision.transforms import RandomResizedCrop, RandomCrop
from torchvision.transforms import InterpolationMode
def rescale(img, bboxes, target_size=2240):
h, w = img.shape[0:2... | 176 | 5,316 |
EasyOCR | trainer/craft/data/boxEnlarge.py | .py | import math
import numpy as np
def pointAngle(Apoint, Bpoint):
angle = (Bpoint[1] - Apoint[1]) / ((Bpoint[0] - Apoint[0]) + 10e-8)
return angle
def pointDistance(Apoint, Bpoint):
return math.sqrt((Bpoint[1] - Apoint[1])**2 + (Bpoint[0] - Apoint[0])**2)
def lineBiasAndK(Apoint, Bpoint):
K = pointAng... | 65 | 2,247 |
EasyOCR | trainer/craft/data/dataset.py | .py | import os
import re
import itertools
import random
import numpy as np
import scipy.io as scio
from PIL import Image
import cv2
from torch.utils.data import Dataset
import torchvision.transforms as transforms
from data import imgproc
from data.gaussian import GaussianBuilder
from data.imgaug import (
rescale,
... | 543 | 17,766 |
EasyOCR | trainer/craft/data/pseudo_label/watershed.py | .py | import cv2
import numpy as np
from skimage.segmentation import watershed
def segment_region_score(watershed_param, region_score, word_image, pseudo_vis_opt):
region_score = np.float32(region_score) / 255
fore = np.uint8(region_score > 0.75)
back = np.uint8(region_score < 0.05)
unknown = 1 - (fore + ba... | 46 | 1,353 |
EasyOCR | trainer/craft/data/pseudo_label/make_charbox.py | .py | import os
import random
import math
import numpy as np
import cv2
import torch
from data import imgproc
from data.pseudo_label.watershed import exec_watershed_by_version
class PseudoCharBoxBuilder:
def __init__(self, watershed_param, vis_test_dir, pseudo_vis_opt, gaussian_builder):
self.watershed_param ... | 264 | 9,045 |
EasyOCR | trainer/modules/prediction.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
class Attention(nn.Module):
def __init__(self, input_size, hidden_size, num_classes):
super(Attention, self).__init__()
self.attention_cell = AttentionCell(inpu... | 82 | 4,026 |
EasyOCR | trainer/modules/feature_extraction.py | .py | import torch.nn as nn
import torch.nn.functional as F
class VGG_FeatureExtractor(nn.Module):
""" FeatureExtractor of CRNN (https://arxiv.org/pdf/1507.05717.pdf) """
def __init__(self, input_channel, output_channel=512):
super(VGG_FeatureExtractor, self).__init__()
self.output_channel = [int(o... | 247 | 10,366 |
EasyOCR | trainer/modules/transformation.py | .py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
class TPS_SpatialTransformerNetwork(nn.Module):
""" Rectification Network of RARE, namely TPS based STN """
def __init__(self, F, I_size, I_r_size, I_cha... | 161 | 8,116 |
EasyOCR | trainer/modules/sequence_modeling.py | .py | import torch.nn as nn
class BidirectionalLSTM(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(BidirectionalLSTM, self).__init__()
self.rnn = nn.LSTM(input_size, hidden_size, bidirectional=True, batch_first=True)
self.linear = nn.Linear(hidden_size * 2, output_s... | 23 | 796 |
EasyOCR | unit_test/make_test_solution.py | .py | import os
import argparse
import lzma
import pickle
from datetime import datetime
import numpy as np
import PIL.Image
import torch
import easyocr
# %%
def count_parameters(model):
return sum([param.numel() for param in model.parameters()])
def get_weight_norm(model):
with torch.no_grad():
return sum... | 648 | 24,942 |
EasyOCR | unit_test/demo.py | .py | import os
from unit_test import UnitTest
# %% Set up paths
easyocr_module = "../easyocr"
verbose = 2
test_data = "./data/EasyOcrUnitTestPackage.pickle"
image_data_dir = "../examples"
# %% Initialize UnitTest
unit_test = UnitTest(easyocr_module,
test_data,
image_data_dir
... | 16 | 409 |
EasyOCR | unit_test/unit_test.py | .py | import os
import sys
import importlib
import pickle
import lzma
import PIL.Image
import numpy as np
import torch
# %%
class Attributes:
pass
class UnitTest:
def __init__(self,
easyocr_module,
test_data = "./data/EasyOcrUnitTestPackage.pickle",
image_data_d... | 262 | 10,576 |
EasyOCR | unit_test/run_unit_test.py | .py |
import argparse
from unit_test import UnitTest
# %%
def main(args):
unit_test = UnitTest(args.easyocr, args.test_data, args.image_data_dir, args.verbose)
unit_test.do_test(args.verbose)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Script to run EasyOCR unit tet.",
... | 20 | 882 |
EasyOCR | easyocr/craft_utils.py | .py | """
Copyright (c) 2019-present NAVER Corp.
MIT License
"""
# -*- coding: utf-8 -*-
import numpy as np
import cv2
import math
from scipy.ndimage import label
""" auxiliary functions """
# unwarp corodinates
def warpCoord(Minv, pt):
out = np.matmul(Minv, (pt[0], pt[1], 1))
return np.array([out[0]/out[2], out[... | 252 | 9,583 |
EasyOCR | easyocr/imgproc.py | .py | """
Copyright (c) 2019-present NAVER Corp.
MIT License
"""
# -*- coding: utf-8 -*-
import numpy as np
from skimage import io
import cv2
def loadImage(img_file):
img = io.imread(img_file) # RGB order
if img.shape[0] == 2: img = img[0]
if len(img.shape) == 2 : img = cv2.cvtColor(img, cv2.COLOR_G... | 71 | 2,195 |
EasyOCR | easyocr/utils.py | .py | from __future__ import print_function
import torch
import pickle
import numpy as np
import math
import cv2
from PIL import Image, JpegImagePlugin
from scipy import ndimage
import hashlib
import sys, os
from zipfile import ZipFile
from .imgproc import loadImage
if sys.version_info[0] == 2:
from six.moves.urllib.re... | 836 | 34,062 |
EasyOCR | easyocr/export.py | .py | import argparse
import onnx
import torch
import easyocr
import numpy as np
def export_detector(detector_onnx_save_path,
in_shape=[1, 3, 608, 800],
lang_list=["en"],
model_storage_directory=None,
user_network_directory=None,
... | 128 | 5,682 |
EasyOCR | easyocr/__init__.py | .py | from .easyocr import Reader
__version__ = '1.7.2'
| 4 | 51 |
EasyOCR | easyocr/easyocr.py | .py | # -*- coding: utf-8 -*-
from .recognition import get_recognizer, get_text
from .utils import group_text_box, get_image_list, calculate_md5, get_paragraph,\
download_and_unzip, printProgressBar, diff, reformat_input,\
make_rotated_img_list, set_result_with_confidence,\
... | 580 | 31,891 |
EasyOCR | easyocr/detection_db.py | .py | '''
Created by Jaided AI
Released Date: 18/08/2022
Description:
A wrapper for DBNet text detection module for EasyOCR
'''
import os
import numpy as np
import torch
import torch.backends.cudnn as cudnn
from .DBNet.DBNet import DBNet
def test_net(image,
detector,
threshold = 0.2,
... | 221 | 8,772 |
EasyOCR | easyocr/recognition.py | .py | from PIL import Image
import torch
import torch.backends.cudnn as cudnn
import torch.utils.data
import torch.nn.functional as F
import torchvision.transforms as transforms
import numpy as np
from collections import OrderedDict
import importlib
from .utils import CTCLabelConverter
import math
def custom_mean(x):
re... | 234 | 9,353 |
EasyOCR | easyocr/craft.py | .py | """
Copyright (c) 2019-present NAVER Corp.
MIT License
"""
# -*- coding: utf-8 -*-
import torch
import torch.nn as nn
import torch.nn.functional as F
from .model.modules import vgg16_bn, init_weights
class double_conv(nn.Module):
def __init__(self, in_ch, mid_ch, out_ch):
super(double_conv, self).__init_... | 81 | 2,590 |
EasyOCR | easyocr/detection.py | .py | import torch
import torch.backends.cudnn as cudnn
from torch.autograd import Variable
from PIL import Image
from collections import OrderedDict
import cv2
import numpy as np
from .craft_utils import getDetBoxes, adjustResultCoordinates
from .imgproc import resize_aspect_ratio, normalizeMeanVariance
from .craft import ... | 111 | 4,222 |
EasyOCR | easyocr/cli.py | .py | import argparse
import easyocr
def parse_args():
parser = argparse.ArgumentParser(description="Process EasyOCR.")
parser.add_argument(
"-l",
"--lang",
nargs='+',
required=True,
type=str,
help="for languages",
)
parser.add_argument(
"--gpu",
... | 284 | 8,659 |
EasyOCR | easyocr/config.py | .py | import os
os.environ["LRU_CACHE_CAPACITY"] = "1"
BASE_PATH = os.path.dirname(__file__)
MODULE_PATH = os.environ.get("EASYOCR_MODULE_PATH") or \
os.environ.get("MODULE_PATH") or \
os.path.expanduser("~/.EasyOCR/")
# detector parameters
detection_models = {
'craft' : {
'filename... | 212 | 91,824 |
EasyOCR | easyocr/DBNet/DBNet.py | .py | '''
Created by Jaided AI
Released Date: 18/08/2022
Description:
DBNet text detection module.
Many parts of the codes are adapted from https://github.com/MhLiao/DB
'''
import os
import math
import yaml
from shapely.geometry import Polygon
import PIL.Image
import numpy as np
import cv2
import pyclipper
import torch
fro... | 767 | 28,450 |
EasyOCR | easyocr/DBNet/backbones/resnet.py | .py | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
BatchNorm2d = nn.BatchNorm2d
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet34': 'https://d... | 341 | 12,428 |
EasyOCR | easyocr/DBNet/backbones/mobilenetv3.py | .py | # https://github.com/kuan-wang/pytorch-mobilenet-v3
import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = ['MobileNetV3', 'mobilenetv3']
def conv_bn(inp, oup, stride, conv_layer=nn.Conv2d, norm_layer=nn.BatchNorm2d, nlin_layer=nn.ReLU):
return nn.Sequential(
conv_layer(inp, oup, 3... | 253 | 8,930 |
EasyOCR | easyocr/DBNet/decoders/balance_cross_entropy_loss.py | .py | import torch
import torch.nn as nn
class BalanceCrossEntropyLoss(nn.Module):
'''
Balanced cross entropy loss.
Shape:
- Input: :math:`(N, 1, H, W)`
- GT: :math:`(N, 1, H, W)`, same shape as the input
- Mask: :math:`(N, H, W)`, same spatial shape as the input
- Output: scalar... | 57 | 1,954 |
EasyOCR | easyocr/DBNet/decoders/seg_detector_asf.py | .py | from collections import OrderedDict
import pdb
import torch
import torch.nn as nn
from .feature_attention import ScaleFeatureSelection
BatchNorm2d = nn.BatchNorm2d
class SegSpatialScaleDetector(nn.Module):
def __init__(self,
in_channels=[64, 128, 256, 512],
inner_channels=256, k=... | 163 | 7,048 |
EasyOCR | easyocr/DBNet/decoders/feature_attention.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaleChannelAttention(nn.Module):
def __init__(self, in_planes, out_planes, num_features, init_weight=True):
super(ScaleChannelAttention, self).__init__()
self.avgpool = nn.AdaptiveAvgPool2d(1)
print(self.avgpool)
... | 145 | 5,925 |
EasyOCR | easyocr/DBNet/decoders/l1_loss.py | .py | import torch
import torch.nn as nn
class MaskL1Loss(nn.Module):
def __init__(self):
super(MaskL1Loss, self).__init__()
def forward(self, pred: torch.Tensor, gt, mask):
mask_sum = mask.sum()
if mask_sum.item() == 0:
return mask_sum, dict(l1_loss=mask_sum)
else:
... | 42 | 1,363 |
EasyOCR | easyocr/DBNet/decoders/simple_detection.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
from backbones.upsample_head import SimpleUpsampleHead
class SimpleDetectionDecoder(nn.Module):
def __init__(self, feature_channel=256):
nn.Module.__init__(self)
self.feature_channel = feature_channel
self.head_layer = s... | 192 | 6,383 |
EasyOCR | easyocr/DBNet/decoders/pss_loss.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
class PSS_Loss(nn.Module):
def __init__(self, cls_loss):
super(PSS_Loss, self).__init__()
self.eps = 1e-6
self.criterion = eval('self.' + cls_loss + '_loss')
def dice_loss(self, pred, gt, m):
intersection = tor... | 116 | 4,582 |
EasyOCR | easyocr/DBNet/decoders/seg_detector.py | .py | from collections import OrderedDict
import torch
import torch.nn as nn
BatchNorm2d = nn.BatchNorm2d
class SegDetector(nn.Module):
def __init__(self,
in_channels=[64, 128, 256, 512],
inner_channels=256, k=10,
bias=False, adaptive=False, smooth=False, serial=False,... | 153 | 6,112 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.