| Name | ocrvid JSON |
| Version |
0.5.3
JSON |
| download |
| home_page | |
| Summary | CLI tool for OCR-ing video frames on macOS |
| upload_time | 2024-02-21 14:50:53 |
| maintainer | |
| docs_url | None |
| author | kj-9 |
| requires_python | >=3.8 |
| license | Apache-2.0 |
| keywords |
ocr
macos
video
movie
cli
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# ocrvid
[](https://pypi.org/project/ocrvid/)
[](https://github.com/kj-9/ocrvid/releases)
[](https://github.com/kj-9/ocrvid/actions?query=workflow%3ACI)
[](https://github.com/kj-9/ocrvid/blob/master/LICENSE)
CLI tool to extract text from videos using OCR on macOS.
> [!NOTE]
> Currently, this tool only tested and works on macOS 13 or later.
> [!CAUTION]
> This tool is still in early development stage. Current v0.x releases are not stable and may have breaking changes.
## Installation
Install this tool using `pip`:
pip install ocrvid
## Usage
<!-- [[[cog
import cog
from ocrvid import cli
from click.testing import CliRunner
runner = CliRunner()
result = runner.invoke(cli.cli, ["--help"])
help = result.output.replace("Usage: cli", "Usage: ocrvid")
cog.out(
f"```\n{help}\n```"
)
]]] -->
```
Usage: ocrvid [OPTIONS] COMMAND [ARGS]...
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
detect Run OCR on a single picture, and print the results as json
langs Show supported recognition languages
props Show properties of video file
run Run OCR on a video, and save result as a json file
```
<!-- [[[end]]] -->
### Run OCR on a video
Use `ocr run` sub command to run ocr on a video file:
<!-- [[[cog
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--help"])
help = result.output.replace("Usage: cli", "Usage: ocrvid")
cog.out(
f"```\n{help}\n```"
)
]]] -->
```
Usage: ocrvid run [OPTIONS] INPUT_VIDEO
Run OCR on a video, and save result as a json file
Options:
-o, --output FILE Path to output json file. By default, if you run
`ocrvid run some/video.mp4` then the output file
will be `./video.json`
-fd, --frames-dir DIRECTORY If passed, then save video frames to this
directory. By default, frames are not saved.
-fs, --frame-step INTEGER Number of frames to skip between each frame to be
processed. By default, 100 which means every 100
frames, 1 frame will be processed.
-bs, --by-second FLOAT If passed, then process 1 frame every N seconds.
This option relies on fps metadata of the video.
-l, --langs TEXT Prefered languages to detect, ordered by
priority. See avalable languages run by `ocrvid
langs`. If not passed, language is auto detected.
--help Show this message and exit.
```
<!-- [[[end]]] -->
For example, run against the test video file at `tests/video/pexels-eva-elijas.mp4` in this repo:
```
ocrvid run tests/video/pexels-eva-elijas.mp4
```
Then `pexels-eva-elija.json` is generated in the current directory which looks like this:
```json
{
"video_file":"tests/video/pexels-eva-elijas.mp4",
"frames":[
{
"frame_index":0,
"results":[
{
"text":"INSPIRING WORDS",
"confidence":1.0,
"bbox":[
0.17844826551211515,
0.7961793736859821,
0.3419540405273438,
0.10085802570754931
]
},
{
"text":"\"Foar kills more dre",
"confidence":1.0,
"bbox":[
0.0724226723609706,
0.6839455987759758,
0.4780927975972494,
0.14592710683043575
]
},
{
"text":"than failure ever",
"confidence":1.0,
"bbox":[
0.018455287246445035,
0.6549868414269003,
0.45329265594482426,
0.14363905857426462
]
},
{
"text":"IZY KASSEM",
"confidence":0.5,
"bbox":[
-0.015967150208537523,
0.6675747977206025,
0.23065692583719888,
0.08114868486431293
]
},
{
"text":"Entrepreneur",
"confidence":1.0,
"bbox":[
0.01941176222542875,
0.1353812367971159,
0.9058370590209961,
0.26137274083956863
]
}
]
},
...
```
### Show supported languages
You can run `ocrvid langs` to show supported languages to detect.
Results may change depending on running macos version.
On macOS version:
<!-- [[[cog
import platform
cog.out(
f"""```\n{platform.mac_ver()[0]=}\n```""")
]]] -->
```
platform.mac_ver()[0]='14.2.1'
```
<!-- [[[end]]] -->
Result of `ocrvid langs`:
<!-- [[[cog
runner = CliRunner()
result = runner.invoke(cli.cli, ["langs"])
help = result.output.replace("Usage: cli", "Usage: ocrvid")
cog.out(
f"```\n{help}\n```"
)
]]] -->
```
en-US
fr-FR
it-IT
de-DE
es-ES
pt-BR
zh-Hans
zh-Hant
yue-Hans
yue-Hant
ko-KR
ja-JP
ru-RU
uk-UA
th-TH
vi-VT
```
<!-- [[[end]]] -->
## How can I run OCR on YouTube videos?
Take a look at [yt-dlp](https://github.com/yt-dlp/yt-dlp).
## Development
To contribute to this tool, first checkout the code. Then create a new virtual environment:
cd ocrvid
python -m venv venv
source venv/bin/activate
Now install the dependencies and test dependencies:
pip install -e '.[test]'
To run the tests:
make test
Raw data
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"description": "# ocrvid\n\n[](https://pypi.org/project/ocrvid/)\n[](https://github.com/kj-9/ocrvid/releases)\n[](https://github.com/kj-9/ocrvid/actions?query=workflow%3ACI)\n[](https://github.com/kj-9/ocrvid/blob/master/LICENSE)\n\n\nCLI tool to extract text from videos using OCR on macOS.\n\n\n> [!NOTE]\n> Currently, this tool only tested and works on macOS 13 or later.\n\n\n> [!CAUTION]\n> This tool is still in early development stage. Current v0.x releases are not stable and may have breaking changes.\n\n## Installation\n\nInstall this tool using `pip`:\n\n pip install ocrvid\n\n\n## Usage\n\n<!-- [[[cog\nimport cog\nfrom ocrvid import cli\nfrom click.testing import CliRunner\nrunner = CliRunner()\nresult = runner.invoke(cli.cli, [\"--help\"])\nhelp = result.output.replace(\"Usage: cli\", \"Usage: ocrvid\")\ncog.out(\n f\"```\\n{help}\\n```\"\n)\n]]] -->\n```\nUsage: ocrvid [OPTIONS] COMMAND [ARGS]...\n\nOptions:\n --version Show the version and exit.\n --help Show this message and exit.\n\nCommands:\n detect Run OCR on a single picture, and print the results as json\n langs Show supported recognition languages\n props Show properties of video file\n run Run OCR on a video, and save result as a json file\n\n```\n<!-- [[[end]]] -->\n\n### Run OCR on a video\n\nUse `ocr run` sub command to run ocr on a video file:\n\n<!-- [[[cog\nrunner = CliRunner()\nresult = runner.invoke(cli.cli, [\"run\", \"--help\"])\nhelp = result.output.replace(\"Usage: cli\", \"Usage: ocrvid\")\ncog.out(\n f\"```\\n{help}\\n```\"\n)\n]]] -->\n```\nUsage: ocrvid run [OPTIONS] INPUT_VIDEO\n\n Run OCR on a video, and save result as a json file\n\nOptions:\n -o, --output FILE Path to output json file. By default, if you run\n `ocrvid run some/video.mp4` then the output file\n will be `./video.json`\n -fd, --frames-dir DIRECTORY If passed, then save video frames to this\n directory. By default, frames are not saved.\n -fs, --frame-step INTEGER Number of frames to skip between each frame to be\n processed. By default, 100 which means every 100\n frames, 1 frame will be processed.\n -bs, --by-second FLOAT If passed, then process 1 frame every N seconds.\n This option relies on fps metadata of the video.\n -l, --langs TEXT Prefered languages to detect, ordered by\n priority. See avalable languages run by `ocrvid\n langs`. If not passed, language is auto detected.\n --help Show this message and exit.\n\n```\n<!-- [[[end]]] -->\n\nFor example, run against the test video file at `tests/video/pexels-eva-elijas.mp4` in this repo:\n\n```\nocrvid run tests/video/pexels-eva-elijas.mp4\n```\n\nThen `pexels-eva-elija.json` is generated in the current directory which looks like this:\n\n```json\n{\n \"video_file\":\"tests/video/pexels-eva-elijas.mp4\",\n \"frames\":[\n {\n \"frame_index\":0,\n \"results\":[\n {\n \"text\":\"INSPIRING WORDS\",\n \"confidence\":1.0,\n \"bbox\":[\n 0.17844826551211515,\n 0.7961793736859821,\n 0.3419540405273438,\n 0.10085802570754931\n ]\n },\n {\n \"text\":\"\\\"Foar kills more dre\",\n \"confidence\":1.0,\n \"bbox\":[\n 0.0724226723609706,\n 0.6839455987759758,\n 0.4780927975972494,\n 0.14592710683043575\n ]\n },\n {\n \"text\":\"than failure ever\",\n \"confidence\":1.0,\n \"bbox\":[\n 0.018455287246445035,\n 0.6549868414269003,\n 0.45329265594482426,\n 0.14363905857426462\n ]\n },\n {\n \"text\":\"IZY KASSEM\",\n \"confidence\":0.5,\n \"bbox\":[\n -0.015967150208537523,\n 0.6675747977206025,\n 0.23065692583719888,\n 0.08114868486431293\n ]\n },\n {\n \"text\":\"Entrepreneur\",\n \"confidence\":1.0,\n \"bbox\":[\n 0.01941176222542875,\n 0.1353812367971159,\n 0.9058370590209961,\n 0.26137274083956863\n ]\n }\n ]\n },\n...\n```\n\n\n### Show supported languages\n\nYou can run `ocrvid langs` to show supported languages to detect.\nResults may change depending on running macos version.\n\nOn macOS version:\n<!-- [[[cog\nimport platform\ncog.out(\n f\"\"\"```\\n{platform.mac_ver()[0]=}\\n```\"\"\")\n]]] -->\n```\nplatform.mac_ver()[0]='14.2.1'\n```\n<!-- [[[end]]] -->\n\n\nResult of `ocrvid langs`:\n<!-- [[[cog\nrunner = CliRunner()\nresult = runner.invoke(cli.cli, [\"langs\"])\nhelp = result.output.replace(\"Usage: cli\", \"Usage: ocrvid\")\ncog.out(\n f\"```\\n{help}\\n```\"\n)\n]]] -->\n```\nen-US\nfr-FR\nit-IT\nde-DE\nes-ES\npt-BR\nzh-Hans\nzh-Hant\nyue-Hans\nyue-Hant\nko-KR\nja-JP\nru-RU\nuk-UA\nth-TH\nvi-VT\n\n```\n<!-- [[[end]]] -->\n\n## How can I run OCR on YouTube videos?\n\nTake a look at [yt-dlp](https://github.com/yt-dlp/yt-dlp).\n\n\n## Development\n\nTo contribute to this tool, first checkout the code. Then create a new virtual environment:\n\n cd ocrvid\n python -m venv venv\n source venv/bin/activate\n\nNow install the dependencies and test dependencies:\n\n pip install -e '.[test]'\n\nTo run the tests:\n\n make test\n",
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