From f9b83350ab94c067b1921768b80743fde694bc73 Mon Sep 17 00:00:00 2001
From: Yoann Schneider <yschneider@teklia.com>
Date: Mon, 14 Nov 2022 17:40:51 +0100
Subject: [PATCH] remove not needed files, reorganize inside dan module
---
.../dataset_formatters/bessin_formatter.py | 133 -----------------
.../dataset_formatters/synist_formatter.py | 137 ------------------
dan/cli.py | 4 +-
dan/datasets/extract/arkindex_utils.py | 1 -
dan/datasets/extract/extract_from_arkindex.py | 8 -
dan/datasets/extract/utils.py | 26 +++-
dan/datasets/format/bessin.py | 113 +++++++++++++++
dan/datasets/format/synist.py | 120 +++++++++++++++
dan/datasets/utils.py | 33 +++++
dan/decoder.py | 1 -
dan/ocr/train.py | 3 +-
prediction-requirements.txt | 8 -
requirements.txt | 8 +
setup.py | 1 -
14 files changed, 303 insertions(+), 293 deletions(-)
delete mode 100644 Datasets/dataset_formatters/bessin_formatter.py
delete mode 100644 Datasets/dataset_formatters/synist_formatter.py
create mode 100644 dan/datasets/format/bessin.py
create mode 100644 dan/datasets/format/synist.py
delete mode 100644 prediction-requirements.txt
diff --git a/Datasets/dataset_formatters/bessin_formatter.py b/Datasets/dataset_formatters/bessin_formatter.py
deleted file mode 100644
index c7c3db66..00000000
--- a/Datasets/dataset_formatters/bessin_formatter.py
+++ /dev/null
@@ -1,133 +0,0 @@
-# contributors :
-# - Denis Coquenet
-#
-#
-# This software is a computer program written in Python whose purpose is to
-# provide public implementation of deep learning works, in pytorch.
-#
-# This software is governed by the CeCILL-C license under French law and
-# abiding by the rules of distribution of free software. You can use,
-# modify and/ or redistribute the software under the terms of the CeCILL-C
-# license as circulated by CEA, CNRS and INRIA at the following URL
-# "http://www.cecill.info".
-#
-# As a counterpart to the access to the source code and rights to copy,
-# modify and redistribute granted by the license, users are provided only
-# with a limited warranty and the software's author, the holder of the
-# economic rights, and the successive licensors have only limited
-# liability.
-#
-# In this respect, the user's attention is drawn to the risks associated
-# with loading, using, modifying and/or developing or reproducing the
-# software by the user in light of its specific status of free software,
-# that may mean that it is complicated to manipulate, and that also
-# therefore means that it is reserved for developers and experienced
-# professionals having in-depth computer knowledge. Users are therefore
-# encouraged to load and test the software's suitability as regards their
-# requirements in conditions enabling the security of their systems and/or
-# data to be ensured and, more generally, to use and operate it in the
-# same conditions as regards security.
-#
-# The fact that you are presently reading this means that you have had
-# knowledge of the CeCILL-C license and that you accept its terms.
-
-from Datasets.dataset_formatters.generic_dataset_formatter import OCRDatasetFormatter
-import os
-import numpy as np
-from Datasets.dataset_formatters.utils_dataset import natural_sort
-from PIL import Image
-import xml.etree.ElementTree as ET
-import re
-from tqdm import tqdm
-from collections import Counter
-
-
-def remove_spaces(text):
- # remove begin/ending spaces
- text = text.strip()
- # replace \t with regular space
- text = re.sub("\t", " ", text)
- # remove consecutive spaces
- text = re.sub(" +", " ", text)
-# text = text.encode('ascii', 'ignore').decode("utf-8")
- return text
-
-
-class SynistDatasetFormatter(OCRDatasetFormatter):
- def __init__(self, level, set_names=["train", "valid", "test"], dpi=150, sem_token=False):
- super(SynistDatasetFormatter, self).__init__("bessin", level, "_sem" if sem_token else "", set_names)
-
- self.dpi = dpi
- self.counter = Counter()
- self.map_datasets_files.update({
- "bessin": {
- # (1,050 for train, 100 for validation and 100 for test)
- "line": {
- "needed_files": [],
- "arx_files": [],
- "format_function": self.format_bessin_zone
- }
- }
- })
-
- def preformat_bessin_zone(self):
- """
- Extract all information from dataset and correct some annotations
- """
-
- dataset = {
- "train": list(),
- "valid": list(),
- "test": list()
- }
- img_folder_path = os.path.join("Datasets", "raw", "bessin", "images")
- labels_folder_path = os.path.join("Datasets", "raw", "bessin", "labels")
-
- train_files = [
- os.path.join(labels_folder_path, 'train', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'train'))]
- valid_files = [
- os.path.join(labels_folder_path, 'valid', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'valid'))]
- test_files = [
- os.path.join(labels_folder_path, 'test', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'test'))]
-
- for set_name, files in zip(self.set_names, [train_files, valid_files, test_files]):
- for i, label_file in enumerate(tqdm(files, desc='Pre-formatting '+set_name)):
- with open(label_file, 'r') as f:
- text = remove_spaces(f.read())
-
- dataset[set_name].append({
- "img_path": os.path.join(
- img_folder_path, set_name, label_file.split('/')[-1].replace('txt', 'jpg')),
- "label": text.strip()
- })
-
- return dataset
-
- def format_bessin_zone(self):
- """
- Format synist page dataset
- """
- dataset = self.preformat_bessin_zone()
- for set_name in self.set_names:
- fold = os.path.join(self.target_fold_path, set_name)
- for sample in tqdm(dataset[set_name], desc='Formatting '+set_name):
- new_name = sample['img_path'].split('/')[-1]
- new_img_path = os.path.join(fold, new_name)
- self.load_resize_save(sample["img_path"], new_img_path)
- zone = {
- "text": sample["label"],
- }
- self.charset = self.charset.union(set(zone["text"]))
- self.gt[set_name][new_name] = zone
- self.counter.update(zone['text'])
-
-
-if __name__ == "__main__":
- formatter = SynistDatasetFormatter("line", sem_token=False)
- formatter.format()
- print("Character freq: ")
- for k,v in formatter.counter.items():
- print(k, v)
\ No newline at end of file
diff --git a/Datasets/dataset_formatters/synist_formatter.py b/Datasets/dataset_formatters/synist_formatter.py
deleted file mode 100644
index c028ee73..00000000
--- a/Datasets/dataset_formatters/synist_formatter.py
+++ /dev/null
@@ -1,137 +0,0 @@
-# contributors :
-# - Denis Coquenet
-#
-#
-# This software is a computer program written in Python whose purpose is to
-# provide public implementation of deep learning works, in pytorch.
-#
-# This software is governed by the CeCILL-C license under French law and
-# abiding by the rules of distribution of free software. You can use,
-# modify and/ or redistribute the software under the terms of the CeCILL-C
-# license as circulated by CEA, CNRS and INRIA at the following URL
-# "http://www.cecill.info".
-#
-# As a counterpart to the access to the source code and rights to copy,
-# modify and redistribute granted by the license, users are provided only
-# with a limited warranty and the software's author, the holder of the
-# economic rights, and the successive licensors have only limited
-# liability.
-#
-# In this respect, the user's attention is drawn to the risks associated
-# with loading, using, modifying and/or developing or reproducing the
-# software by the user in light of its specific status of free software,
-# that may mean that it is complicated to manipulate, and that also
-# therefore means that it is reserved for developers and experienced
-# professionals having in-depth computer knowledge. Users are therefore
-# encouraged to load and test the software's suitability as regards their
-# requirements in conditions enabling the security of their systems and/or
-# data to be ensured and, more generally, to use and operate it in the
-# same conditions as regards security.
-#
-# The fact that you are presently reading this means that you have had
-# knowledge of the CeCILL-C license and that you accept its terms.
-
-from Datasets.dataset_formatters.generic_dataset_formatter import OCRDatasetFormatter
-import os
-import numpy as np
-from Datasets.dataset_formatters.utils_dataset import natural_sort
-from PIL import Image
-import xml.etree.ElementTree as ET
-import re
-from tqdm import tqdm
-from collections import Counter
-
-
-def remove_spaces(text):
- # remove begin/ending spaces
- text = text.strip()
- # replace \t with regular space
- text = re.sub("\t", " ", text)
- # remove consecutive spaces
- text = re.sub(" +", " ", text)
-# text = text.encode('ascii', 'ignore').decode("utf-8")
- return text
-
-
-class SynistDatasetFormatter(OCRDatasetFormatter):
- def __init__(self, level, set_names=["train", "valid", "test"], dpi=150, sem_token=False):
- super(SynistDatasetFormatter, self).__init__("synist_synth", level, "_sem" if sem_token else "", set_names)
-
- self.dpi = dpi
- self.counter = Counter()
- self.map_datasets_files.update({
- "synist_synth": {
- # (1,050 for train, 100 for validation and 100 for test)
- "line": {
- "needed_files": [],
- "arx_files": [],
- "format_function": self.format_synist_page
- }
- }
- })
-
- def preformat_synist_page(self):
- """
- Extract all information from dataset and correct some annotations
- """
-
- dataset = {
- "train": list(),
- "valid": list(),
- "test": list()
- }
- img_folder_path = os.path.join("Datasets", "raw", "synist_synth_lines", "images")
- labels_folder_path = os.path.join("Datasets", "raw", "synist_synth_lines", "labels")
-
- train_files = [
- os.path.join(labels_folder_path, 'train', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'train'))]
- valid_files = [
- os.path.join(labels_folder_path, 'valid', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'valid'))]
- test_files = [
- os.path.join(labels_folder_path, 'test', name)
- for name in os.listdir(os.path.join(labels_folder_path, 'test'))]
-
- for set_name, files in zip(self.set_names, [train_files, valid_files, test_files]):
- for i, label_file in enumerate(tqdm(files, desc='Pre-formatting '+set_name)):
- with open(label_file, 'r') as f:
- text = remove_spaces(f.read())
-
- dataset[set_name].append({
- "img_path": os.path.join(
- img_folder_path, set_name, label_file.split('/')[-1].replace('txt', 'png')),
- "label": text.strip()
- })
-
- return dataset
-
- def format_synist_page(self):
- """
- Format synist page dataset
- """
- dataset = self.preformat_synist_page()
- for set_name in self.set_names:
- fold = os.path.join(self.target_fold_path, set_name)
- for sample in tqdm(dataset[set_name], desc='Formatting '+set_name):
- new_name = sample['img_path'].split('/')[-1]
- new_img_path = os.path.join(fold, new_name)
- #self.load_resize_save(sample["img_path"], new_img_path, 300, self.dpi)
- self.load_resize_save(sample["img_path"], new_img_path)
- #self.load_flip_save(new_img_path, new_img_path)
- page = {
- "text": sample["label"],
- }
- self.charset = self.charset.union(set(page["text"]))
- self.gt[set_name][new_name] = page
- self.counter.update(page['text'])
-
-
-if __name__ == "__main__":
- formatter = SynistDatasetFormatter("line", sem_token=False)
- formatter.format()
- print(formatter.counter)
- print(formatter.counter.most_common(80))
- for k,v in formatter.counter.items():
- print(k)
- print(k.encode('utf-8'), v)
diff --git a/dan/cli.py b/dan/cli.py
index b0ed2199..fff057b9 100644
--- a/dan/cli.py
+++ b/dan/cli.py
@@ -1,13 +1,12 @@
# -*- coding: utf-8 -*-
import argparse
import errno
+
from dan.datasets.extract.extract_from_arkindex import add_extract_parser
from dan.ocr.line.generate_synthetic import add_generate_parser
-
from dan.ocr.train import add_train_parser
-
def get_parser():
parser = argparse.ArgumentParser(prog="TEKLIA DAN training")
subcommands = parser.add_subparsers(metavar="subcommand")
@@ -17,6 +16,7 @@ def get_parser():
add_generate_parser(subcommands)
return parser
+
def main():
parser = get_parser()
args = vars(parser.parse_args())
diff --git a/dan/datasets/extract/arkindex_utils.py b/dan/datasets/extract/arkindex_utils.py
index 5216a7e0..d9d2e065 100644
--- a/dan/datasets/extract/arkindex_utils.py
+++ b/dan/datasets/extract/arkindex_utils.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
diff --git a/dan/datasets/extract/extract_from_arkindex.py b/dan/datasets/extract/extract_from_arkindex.py
index 1a6e207d..c9c1c2c1 100644
--- a/dan/datasets/extract/extract_from_arkindex.py
+++ b/dan/datasets/extract/extract_from_arkindex.py
@@ -1,12 +1,4 @@
-#!/usr/bin/env python
# -*- coding: utf-8 -*-
-#
-# Example of minimal usage:
-# python extract_from_arkindex.py
-# --corpus "AN-Simara annotations E (2022-06-20)"
-# --parents-types folder
-# --parents-names FRAN_IR_032031_4538.pdf
-# --output-dir ../
"""
The extraction module
diff --git a/dan/datasets/extract/utils.py b/dan/datasets/extract/utils.py
index 72ab461b..77d15804 100644
--- a/dan/datasets/extract/utils.py
+++ b/dan/datasets/extract/utils.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@@ -25,6 +24,13 @@ def get_cli_args():
help="Name of the corpus from which the data will be retrieved.",
required=True,
)
+ parser.add_argument(
+ "--element-type",
+ nargs="+",
+ type=str,
+ help="Type of elements to retrieve",
+ required=True,
+ )
parser.add_argument(
"--parents-types",
nargs="+",
@@ -47,4 +53,22 @@ def get_cli_args():
help="Names of parents of the elements.",
default=None,
)
+ parser.add_argument(
+ "--no-entities", action="store_true", help="Extract text without entities"
+ )
+
+ parser.add_argument(
+ "--use-existing-split",
+ action="store_true",
+ help="Do not partition pages into train/val/test",
+ )
+
+ parser.add_argument(
+ "--train-prob", type=float, default=0.7, help="Training set probability"
+ )
+
+ parser.add_argument(
+ "--val-prob", type=float, default=0.15, help="Validation set probability"
+ )
+
return parser.parse_args()
diff --git a/dan/datasets/format/bessin.py b/dan/datasets/format/bessin.py
new file mode 100644
index 00000000..1b2248b2
--- /dev/null
+++ b/dan/datasets/format/bessin.py
@@ -0,0 +1,113 @@
+# -*- coding: utf-8 -*-
+import os
+import re
+from collections import Counter
+
+from tqdm import tqdm
+
+from dan.datasets.format.generic import OCRDatasetFormatter
+
+
+def remove_spaces(text):
+ # remove begin/ending spaces
+ text = text.strip()
+ # replace \t with regular space
+ text = re.sub("\t", " ", text)
+ # remove consecutive spaces
+ text = re.sub(" +", " ", text)
+ # text = text.encode('ascii', 'ignore').decode("utf-8")
+ return text
+
+
+class BessinDatasetFormatter(OCRDatasetFormatter):
+ def __init__(
+ self, level, set_names=["train", "valid", "test"], dpi=150, sem_token=False
+ ):
+ super(BessinDatasetFormatter, self).__init__(
+ "bessin", level, "_sem" if sem_token else "", set_names
+ )
+
+ self.dpi = dpi
+ self.counter = Counter()
+ self.map_datasets_files.update(
+ {
+ "bessin": {
+ # (1,050 for train, 100 for validation and 100 for test)
+ "line": {
+ "needed_files": [],
+ "arx_files": [],
+ "format_function": self.format_bessin_zone,
+ }
+ }
+ }
+ )
+
+ def preformat_bessin_zone(self):
+ """
+ Extract all information from dataset and correct some annotations
+ """
+
+ dataset = {"train": list(), "valid": list(), "test": list()}
+ img_folder_path = os.path.join("Datasets", "raw", "bessin", "images")
+ labels_folder_path = os.path.join("Datasets", "raw", "bessin", "labels")
+
+ train_files = [
+ os.path.join(labels_folder_path, "train", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "train"))
+ ]
+ valid_files = [
+ os.path.join(labels_folder_path, "valid", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "valid"))
+ ]
+ test_files = [
+ os.path.join(labels_folder_path, "test", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "test"))
+ ]
+
+ for set_name, files in zip(
+ self.set_names, [train_files, valid_files, test_files]
+ ):
+ for i, label_file in enumerate(
+ tqdm(files, desc="Pre-formatting " + set_name)
+ ):
+ with open(label_file, "r") as f:
+ text = remove_spaces(f.read())
+
+ dataset[set_name].append(
+ {
+ "img_path": os.path.join(
+ img_folder_path,
+ set_name,
+ label_file.split("/")[-1].replace("txt", "jpg"),
+ ),
+ "label": text.strip(),
+ }
+ )
+
+ return dataset
+
+ def format_bessin_zone(self):
+ """
+ Format synist page dataset
+ """
+ dataset = self.preformat_bessin_zone()
+ for set_name in self.set_names:
+ fold = os.path.join(self.target_fold_path, set_name)
+ for sample in tqdm(dataset[set_name], desc="Formatting " + set_name):
+ new_name = sample["img_path"].split("/")[-1]
+ new_img_path = os.path.join(fold, new_name)
+ self.load_resize_save(sample["img_path"], new_img_path)
+ zone = {
+ "text": sample["label"],
+ }
+ self.charset = self.charset.union(set(zone["text"]))
+ self.gt[set_name][new_name] = zone
+ self.counter.update(zone["text"])
+
+
+if __name__ == "__main__":
+ formatter = BessinDatasetFormatter("line", sem_token=False)
+ formatter.format()
+ print("Character freq: ")
+ for k, v in formatter.counter.items():
+ print(k, v)
diff --git a/dan/datasets/format/synist.py b/dan/datasets/format/synist.py
new file mode 100644
index 00000000..87c18fea
--- /dev/null
+++ b/dan/datasets/format/synist.py
@@ -0,0 +1,120 @@
+# -*- coding: utf-8 -*-
+import os
+import re
+from collections import Counter
+
+from tqdm import tqdm
+
+from dan.datasets.format.generic import OCRDatasetFormatter
+
+
+def remove_spaces(text):
+ # remove begin/ending spaces
+ text = text.strip()
+ # replace \t with regular space
+ text = re.sub("\t", " ", text)
+ # remove consecutive spaces
+ text = re.sub(" +", " ", text)
+ return text
+
+
+class SynistDatasetFormatter(OCRDatasetFormatter):
+ def __init__(
+ self, level, set_names=["train", "valid", "test"], dpi=150, sem_token=False
+ ):
+ super(SynistDatasetFormatter, self).__init__(
+ "synist_synth", level, "_sem" if sem_token else "", set_names
+ )
+
+ self.dpi = dpi
+ self.counter = Counter()
+ self.map_datasets_files.update(
+ {
+ "synist_synth": {
+ # (1,050 for train, 100 for validation and 100 for test)
+ "line": {
+ "needed_files": [],
+ "arx_files": [],
+ "format_function": self.format_synist_page,
+ }
+ }
+ }
+ )
+
+ def preformat_synist_page(self):
+ """
+ Extract all information from dataset and correct some annotations
+ """
+
+ dataset = {"train": list(), "valid": list(), "test": list()}
+ img_folder_path = os.path.join(
+ "Datasets", "raw", "synist_synth_lines", "images"
+ )
+ labels_folder_path = os.path.join(
+ "Datasets", "raw", "synist_synth_lines", "labels"
+ )
+
+ train_files = [
+ os.path.join(labels_folder_path, "train", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "train"))
+ ]
+ valid_files = [
+ os.path.join(labels_folder_path, "valid", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "valid"))
+ ]
+ test_files = [
+ os.path.join(labels_folder_path, "test", name)
+ for name in os.listdir(os.path.join(labels_folder_path, "test"))
+ ]
+
+ for set_name, files in zip(
+ self.set_names, [train_files, valid_files, test_files]
+ ):
+ for i, label_file in enumerate(
+ tqdm(files, desc="Pre-formatting " + set_name)
+ ):
+ with open(label_file, "r") as f:
+ text = remove_spaces(f.read())
+
+ dataset[set_name].append(
+ {
+ "img_path": os.path.join(
+ img_folder_path,
+ set_name,
+ label_file.split("/")[-1].replace("txt", "png"),
+ ),
+ "label": text.strip(),
+ }
+ )
+
+ return dataset
+
+ def format_synist_page(self):
+ """
+ Format synist page dataset
+ """
+ dataset = self.preformat_synist_page()
+ for set_name in self.set_names:
+ fold = os.path.join(self.target_fold_path, set_name)
+ for sample in tqdm(dataset[set_name], desc="Formatting " + set_name):
+ new_name = sample["img_path"].split("/")[-1]
+ new_img_path = os.path.join(fold, new_name)
+ # self.load_resize_save(sample["img_path"], new_img_path, 300, self.dpi)
+ self.load_resize_save(sample["img_path"], new_img_path)
+ # self.load_flip_save(new_img_path, new_img_path)
+ page = {
+ "text": sample["label"],
+ }
+ self.charset = self.charset.union(set(page["text"]))
+ self.gt[set_name][new_name] = page
+ self.counter.update(page["text"])
+
+
+if __name__ == "__main__":
+ formatter = SynistDatasetFormatter("line", sem_token=False)
+ formatter.format()
+ print(formatter.counter)
+ print(formatter.counter.most_common(80))
+ for k, v in formatter.counter.items():
+ print(k)
+ print(k.encode("utf-8"), v)
diff --git a/dan/datasets/utils.py b/dan/datasets/utils.py
index c911cc9b..6422357c 100644
--- a/dan/datasets/utils.py
+++ b/dan/datasets/utils.py
@@ -1,6 +1,12 @@
# -*- coding: utf-8 -*-
+import json
+import random
import re
+import cv2
+
+random.seed(42)
+
def convert(text):
return int(text) if text.isdigit() else text.lower()
@@ -8,3 +14,30 @@ def convert(text):
def natural_sort(data):
return sorted(data, key=lambda key: [convert(c) for c in re.split("([0-9]+)", key)])
+
+
+def assign_random_split(train_prob, val_prob):
+ """
+ assuming train_prob + val_prob + test_prob = 1
+ """
+ prob = random.random()
+ if prob <= train_prob:
+ return "train"
+ elif prob <= train_prob + val_prob:
+ return "val"
+ else:
+ return "test"
+
+
+def save_text(path, text):
+ with open(path, "w") as f:
+ f.write(text)
+
+
+def save_image(path, image):
+ cv2.imwrite(path, cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+
+
+def save_json(path, dict):
+ with open(path, "w") as outfile:
+ json.dump(dict, outfile, indent=4)
diff --git a/dan/decoder.py b/dan/decoder.py
index d2070fc6..f69d8e9a 100644
--- a/dan/decoder.py
+++ b/dan/decoder.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python
# -*- coding: utf-8 -*-
import torch
diff --git a/dan/ocr/train.py b/dan/ocr/train.py
index 1bcbe1c7..dda43ba8 100644
--- a/dan/ocr/train.py
+++ b/dan/ocr/train.py
@@ -1,7 +1,8 @@
# -*- coding: utf-8 -*-
-from dan.ocr.line.train import add_line_parser
from dan.ocr.document.train import add_document_parser
+from dan.ocr.line.train import add_line_parser
+
def add_train_parser(subcommands) -> None:
parser = subcommands.add_parser(
diff --git a/prediction-requirements.txt b/prediction-requirements.txt
deleted file mode 100644
index 86bfaeb8..00000000
--- a/prediction-requirements.txt
+++ /dev/null
@@ -1,8 +0,0 @@
-arkindex-client==1.0.11
-editdistance==0.6.0
-fontTools==4.29.1
-imageio==2.16.0
-networkx==2.6.3
-tensorboard==0.2.1
-torchvision==0.12.0
-tqdm==4.62.3
diff --git a/requirements.txt b/requirements.txt
index 1fe32d37..27758aa6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,12 @@
+arkindex-client==1.0.11
+editdistance==0.6.0
+fontTools==4.29.1
+imageio==2.16.0
+networkx==2.6.3
numpy==1.22.3
opencv-python==4.5.5.64
PyYAML==6.0
+tensorboard==0.2.1
torch==1.11.0
+torchvision==0.12.0
+tqdm==4.62.3
diff --git a/setup.py b/setup.py
index a0002964..51d55e0f 100755
--- a/setup.py
+++ b/setup.py
@@ -28,5 +28,4 @@ setup(
"teklia-dan=dan.cli:main",
]
},
- extras_require={"predict": parse_requirements("prediction-requirements.txt")},
)
--
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