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# Template for your OCR API using docTR
## Installation
You will only need to install [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git), [Docker](https://docs.docker.com/get-docker/) and [poetry](https://python-poetry.org/docs/#installation). The container environment will be self-sufficient and install the remaining dependencies on its own.
## Usage
### Starting your web server
You will need to clone the repository first, go into `api` folder and start the api:
```shell
git clone https://github.com/mindee/doctr.git
cd doctr/api
make run
```
Once completed, your [FastAPI](https://fastapi.tiangolo.com/) server should be running on port 8080.
### Documentation and swagger
FastAPI comes with many advantages including speed and OpenAPI features. For instance, once your server is running, you can access the automatically built documentation and swagger in your browser at: [http://localhost:8080/docs](http://localhost:8080/docs)
### Using the routes
You will find detailed instructions in the live documentation when your server is up, but here are some examples to use your available API routes:
#### Text detection
Using the following image:
<img src="https://user-images.githubusercontent.com/76527547/117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg" width="50%" height="50%">
with this snippet:
```python
import requests
headers = {"accept": "application/json"}
params = {"det_arch": "db_resnet50"}
with open('/path/to/your/img.jpg', 'rb') as f:
files = [ # application/pdf, image/jpeg, image/png supported
("files", ("117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg", f.read(), "image/jpeg")),
]
print(requests.post("http://localhost:8080/detection", headers=headers, params=params, files=files).json())
```
should yield
```json
[
{
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"geometries": [
[
0.8176307908857315,
0.1787109375,
0.9101580212741838,
0.2080078125
],
[
0.7471996155154171,
0.1796875,
0.8272978149561669,
0.20703125
]
]
}
]
```
#### Text recognition
Using the following image:
with this snippet:
```python
import requests
headers = {"accept": "application/json"}
params = {"reco_arch": "crnn_vgg16_bn"}
with open('/path/to/your/img.jpg', 'rb') as f:
files = [ # application/pdf, image/jpeg, image/png supported
("files", ("117133599-c073fa00-ada4-11eb-831b-412de4d28341.jpeg", f.read(), "image/jpeg")),
]
print(requests.post("http://localhost:8080/recognition", headers=headers, params=params, files=files).json())
```
should yield
```json
[
{
"name": "117133599-c073fa00-ada4-11eb-831b-412de4d28341.jpeg",
"value": "invite",
"confidence": 1.0
}
]
```
#### End-to-end OCR
Using the following image:
<img src="https://user-images.githubusercontent.com/76527547/117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg" width="50%" height="50%">
with this snippet:
```python
import requests
headers = {"accept": "application/json"}
params = {"det_arch": "db_resnet50", "reco_arch": "crnn_vgg16_bn"}
with open('/path/to/your/img.jpg', 'rb') as f:
files = [ # application/pdf, image/jpeg, image/png supported
("files", ("117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg", f.read(), "image/jpeg")),
]
print(requests.post("http://localhost:8080/ocr", headers=headers, params=params, files=files).json())
```
should yield
```json
[
{
"name": "117319856-fc35bf00-ae8b-11eb-9b51-ca5aba673466.jpg",
"orientation": {
"value": 0,
"confidence": null
},
"language": {
"value": null,
"confidence": null
},
"dimensions": [2339, 1654],
"items": [
{
"blocks": [
{
"geometry": [
0.7471996155154171,
0.1787109375,
0.9101580212741838,
0.2080078125
],
"objectness_score": 0.5,
"lines": [
{
"geometry": [
0.7471996155154171,
0.1787109375,
0.9101580212741838,
0.2080078125
],
"objectness_score": 0.5,
"words": [
{
"value": "Hello",
"geometry": [
0.7471996155154171,
0.1796875,
0.8272978149561669,
0.20703125
],
"objectness_score": 0.5,
"confidence": 1.0,
"crop_orientation": {"value": 0, "confidence": null}
},
{
"value": "world!",
"geometry": [
0.8176307908857315,
0.1787109375,
0.9101580212741838,
0.2080078125
],
"objectness_score": 0.5,
"confidence": 1.0,
"crop_orientation": {"value": 0, "confidence": null}
}
]
}
]
}
]
}
]
}
]
```
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