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paddlex --get_pipeline_config PP-ShiTuV2
After execution, the General Image Recognition Pipeline configuration file will be saved in the current directory. If you want to customize the save location, you can run the following command (assuming the custom save location is ./my_path):
paddlex --get_pipeline_config PP-ShiTuV2 --save_path ./my_path
API Reference
For main operations provided by the service:
- The HTTP request method is POST.
- The request body and the response body are both JSON data (JSON objects).
- When the request is processed successfully, the response status code is
200, and the response body properties are as follows:
| Name |
Type |
Meaning |
errorCode |
integer |
Error code. Fixed to 0. |
errorMsg |
string |
Error description. Fixed to "Success". |
The response body may also have a result property, which is an object type that stores operation result information.
- When the request is not processed successfully, the properties of the response body are as follows:
| Name |
Type |
Meaning |
errorCode |
integer |
Error code. Same as the response status code. |
errorMsg |
string |
Error description. |
The main operations provided by the service are as follows:
Build feature vector index.
POST /shitu-index-build
- The properties of the request body are as follows:
| Name |
Type |
Meaning |
Required |
imageLabelPairs |
array |
Image-label pairs for building the index. |
Yes |
Each element in imageLabelPairs is an object with the following properties:
| Name |
Type |
Meaning |
image |
string |
The URL of an image file accessible by the service, or the Base64 encoding result of the image file content. |
label |
string |
Label. |
- When the request is processed successfully, the
result of the response body has the following properties:
| Name |
Type |
Meaning |
indexKey |
string |
The key corresponding to the index, used to identify the established index. Can be used as input for other operations. |
idMap |
object |
Mapping from vector ID to label. |
Add images (corresponding feature vectors) to the index.
POST /shitu-index-add
- The properties of the request body are as follows:
| Name |
Type |
Meaning |
Required |
imageLabelPairs |
array |
Image-label pairs for building the index. |
Yes |
indexKey |
string |
The key corresponding to the index. Provided by the buildIndex operation. |
Yes |
Each element in imageLabelPairs is an object with the following properties:
| Name |
Type |
Meaning |
image |
string |
The URL of an image file accessible by the service, or the Base64 encoding result of the image file content. |
label |
string |
Label. |
- When the request is processed successfully, the
result of the response body has the following properties:
| Name |
Type |
Meaning |
idMap |
object |
Mapping from vector ID to label. |
Remove images (corresponding feature vectors) from the index.
POST /shitu-index-remove
- The properties of the request body are as follows:
| Name |
Type |
Meaning |
Required |
ids |
array |
IDs of the vectors to be removed from the index. |
Yes |
indexKey |
string |
The key corresponding to the index. Provided by the buildIndex operation. |
Yes |
- When the request is processed successfully, the
result of the response body has the following properties:
| Name |
Type |
Meaning |
idMap |
object |
Mapping from vector ID to label. |
Perform image recognition.
POST /shitu-infer
- The properties of the request body are as follows:
| Name |
Type |
Meaning |
Required |
image |
string |
The URL of an image file accessible by the service, or the Base64 encoding result of the image file content. |
Yes |
indexKey |
string |
The key corresponding to the index. Provided by the buildIndex operation. |
No |
- When the request is processed successfully, the
result of the response body has the following properties:
| Name |
Type |
Meaning |
detectedObjects |
array |
Information of the detected targets. |
image |
string |
Recognition result image. The image is in JPEG format, encoded with Base64. |
Each element in detectedObjects is an object with the following properties:
| Name |
Type |
Meaning |
bbox |
array |
Target location. The elements in the array are the x-coordinate of the upper-left corner, the y-coordinate of the upper-left corner, the x-coordinate of the lower-right corner, and the y-coordinate of the lower-right corner, respectively. |
recResults |
array |
Recognition results. |
score |
number |
Detection score. |
Each element in recResults is an object with the following properties:
| Name |
Type |
Meaning |
label |
string |
Label. |
score |
number |
Recognition score. |
Multi-Language Service Invocation Examples
Python
import base64
import pprint
import sys
import requests
API_BASE_URL = "http://0.0.0.0:8080"
base_image_label_pairs = [
{"image": "./demo0.jpg", "label": "ε
ε"},
{"image": "./demo1.jpg", "label": "ε
ε"},
{"image": "./demo2.jpg", "label": "ε°η"},
]
image_label_pairs_to_add = [
{"image": "./demo3.jpg", "label": "ε°η"},
]
ids_to_remove = [1]
infer_image_path = "./demo4.jpg"
output_image_path = "./out.jpg"
for pair in base_image_label_pairs:
with open(pair["image"], "rb") as file:
image_bytes = file.read()
image_data = base64.b64encode(image_bytes).decode("ascii")
pair["image"] = image_data
payload = {"imageLabelPairs": base_image_label_pairs}
resp_index_build = requests.post(f"{API_BASE_URL}/shitu-index-build", json=payload)
if resp_index_build.status_code != 200:
print(f"Request to shitu-index-build failed with status code {resp_index_build}.")
pprint.pp(resp_index_build.json())
sys.exit(1)
result_index_build = resp_index_build.json()["result"]
print(f"Number of images indexed: {len(result_index_build['idMap'])}")
for pair in image_label_pairs_to_add:
with open(pair["image"], "rb") as file:
image_bytes = file.read()
image_data = base64.b64encode(image_bytes).decode("ascii")
pair["image"] = image_data
payload = {"imageLabelPairs": image_label_pairs_to_add, "indexKey": result_index_build["indexKey"]}
resp_index_add = requests.post(f"{API_BASE_URL}/shitu-index-add", json=payload)
if resp_index_add.status_code != 200:
print(f"Request to shitu-index-add failed with status code {resp_index_add}.")
pprint.pp(resp_index_add.json())
sys.exit(1)
result_index_add = resp_index_add.json()["result"]
print(f"Number of images indexed: {len(result_index_add['idMap'])}")
payload = {"ids": ids_to_remove, "indexKey": result_index_build["indexKey"]}
resp_index_remove = requests.post(f"{API_BASE_URL}/shitu-index-remove", json=payload)
if resp_index_remove.status_code != 200:
print(f"Request to shitu-index-remove failed with status code {resp_index_remove}.")
pprint.pp(resp_index_remove.json())
sys.exit(1)
result_index_remove = resp_index_remove.json()["result"]
print(f"Number of images indexed: {len(result_index_remove['idMap'])}")
with open(infer_image_path, "rb") as file:
image_bytes = file.read()
image_data = base64.b64encode(image_bytes).decode("ascii")
payload = {"image": image_data, "indexKey": result_index_build["indexKey"]}
resp_infer = requests.post(f"{API_BASE_URL}/shitu-infer", json=payload)
if resp_infer.status_code != 200:
print(f"Request to shitu-infer failed with status code {resp_infer}.")
pprint.pp(resp_infer.json())
sys.exit(1)
result_infer = resp_infer.json()["result"]
with open(output_image_path, "wb") as file:
file.write(base64.b64decode(result_infer["image"]))
print(f"Output image saved at {output_image_path}")
print("\nDetected objects:")
pprint.pp(result_infer["detectedObjects"])
The General Image Recognition Pipeline includes the mainbody detection module and the image feature module, with several models to choose. You can select the model to use based on the benchmark data below. If you prioritize model precision, choose a model with higher precision. If you prioritize inference speed, choose a model with faster inference. If you prioritize model storage size, choose a model with a smaller storage size.
Object Detection Module:
