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4.3 KiB
4.3 KiB
Arcaea Offline OCR
Example
Results from
arcaea_offline_ocr 0.1.0a2
Build an image hash database (ihdb)
import sqlite3
from pathlib import Path
import cv2
from arcaea_offline_ocr.builders.ihdb import (
ImageHashDatabaseBuildTask,
ImageHashesDatabaseBuilder,
)
from arcaea_offline_ocr.providers import ImageCategory, ImageHashDatabaseIdProvider
from arcaea_offline_ocr.scenarios.device import DeviceScenario
def build():
def _read_partner_icon(image_path: str):
return DeviceScenario.preprocess_char_icon(
cv2.cvtColor(cv2.imread(image_path, cv2.IMREAD_COLOR), cv2.COLOR_BGR2GRAY),
)
builder = ImageHashesDatabaseBuilder()
tasks = [
ImageHashDatabaseBuildTask(
image_path=str(file),
image_id=file.stem,
category=ImageCategory.JACKET,
)
for file in Path("/path/to/some/jackets").glob("*.jpg")
]
tasks.extend(
[
ImageHashDatabaseBuildTask(
image_path=str(file),
image_id=file.stem,
category=ImageCategory.PARTNER_ICON,
imread_function=_read_partner_icon,
)
for file in Path("/path/to/some/partner_icons").glob("*.png")
],
)
with sqlite3.connect("/path/to/ihdb-X.Y.Z.db") as conn:
builder.build(conn, tasks)
Device OCR
import json
import sqlite3
from dataclasses import asdict
import cv2
from arcaea_offline_ocr.providers import (
ImageHashDatabaseIdProvider,
OcrKNearestTextProvider,
)
from arcaea_offline_ocr.scenarios.device import (
DeviceRoisAutoT2,
DeviceRoisExtractor,
DeviceRoisMaskerAutoT2,
DeviceScenario,
)
with sqlite3.connect("/path/to/ihdb-X.Y.Z.db") as conn:
img = cv2.imread("/path/to/your/screenshot.jpg")
h, w = img.shape[:2]
r = DeviceRoisAutoT2(w, h)
m = DeviceRoisMaskerAutoT2()
e = DeviceRoisExtractor(img, r)
scenario = DeviceScenario(
extractor=e,
masker=m,
knn_provider=OcrKNearestTextProvider(
cv2.ml.KNearest.load("/path/to/knn_model.dat"),
),
image_id_provider=ImageHashDatabaseIdProvider(conn),
)
result = scenario.result()
with open("result.jsonc", "w", encoding="utf-8") as jf:
json.dump(asdict(result), jf, indent=2, ensure_ascii=False)
// result.json
{
"song_id": "vector",
"rating_class": 1,
"score": 9990996,
"song_id_results": [
{
"image_id": "vector",
"category": 0,
"confidence": 1.0,
"image_hash_type": 0
},
{
"image_id": "clotho",
"category": 0,
"confidence": 0.71875,
"image_hash_type": 0
}
// 28 more results omitted…
],
"partner_id_results": [
{
"image_id": "23",
"category": 1,
"confidence": 0.90625,
"image_hash_type": 0
},
{
"image_id": "45",
"category": 1,
"confidence": 0.8828125,
"image_hash_type": 0
}
// 28 more results omitted…
],
"pure": 1000,
"pure_inaccurate": null,
"pure_early": null,
"pure_late": null,
"far": 2,
"far_inaccurate": null,
"far_early": null,
"far_late": null,
"lost": 0,
"played_at": null,
"max_recall": 1002,
"clear_status": 2,
"clear_type": null,
"modifier": null
}
License
This file is part of arcaea-offline-ocr, as called "This program" below.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.
Credits
- JohannesBuchner/imagehash:
arcaea_offline_ocr.core.hashers
implementations reference