File size: 1,305 Bytes
a0a6251
 
84facbd
 
4cf3b0d
84facbd
 
4cf3b0d
a0a6251
84facbd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4cf3b0d
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
---
license: apache-2.0
tags:
- trocr
- image-classification
- endpoints-template
library_name: generic
pipeline_tag: image-classification
---

## Run Request 

The endpoint expects the image to be served as `binary`. Below is an curl and python example

#### cURL 

1. get image 

```bash
wget https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg -O test.jpg
```

2. send cURL request

```bash
curl --request POST \
  --url https://{ENDPOINT}/ \
  --header 'Content-Type: image/jpg' \
  --header 'Authorization: Bearer {HF_TOKEN}' \
  --data-binary '@test.jpg'
```

3. the expected output

```json
{"text": "INDLUS THE"}
```

#### Python 


1. get image 

```bash
wget https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg -O test.jpg
```

2. run request

```python
import json
from typing import List
import requests as r
import base64

ENDPOINT_URL=""
HF_TOKEN=""

def predict(path_to_image:str=None):
    with open(path_to_image, "rb") as i:
      b = i.read()
    headers= {
        "Authorization": f"Bearer {HF_TOKEN}",
        "Content-Type": "image/jpeg" # content type of image
    }
    response = r.post(ENDPOINT_URL, headers=headers, data=b)
    return response.json()

prediction = predict(path_to_image="test.jpg")

prediction
```

expected output

```python
{"text": "INDLUS THE"}
```