-
-
Save icebeam7/66dee3a4ef04ba2e64437f4ee65d40f6 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import logging | |
import onnxruntime as nxrun | |
import numpy as np | |
import PIL | |
from PIL import Image | |
import requests | |
from io import BytesIO | |
import azure.functions as func | |
def main(req: func.HttpRequest) -> func.HttpResponse: | |
## Obtén la imagen y cambia su tamaño a 244x244 píxeles | |
url = req.params.get('url') | |
response = requests.get(url) | |
image = PIL.Image.open(BytesIO(response.content)).resize([224,224]) | |
## Carga el modelo y puntúa la imagen | |
model_path = "model/model.onnx" | |
sess = nxrun.InferenceSession(model_path) | |
input_array = np.array(image, dtype=np.float32)[np.newaxis, :, :, :] | |
input_array = input_array.transpose((0, 3, 1, 2))[:, (2, 1, 0), :, :] | |
input_name = sess.get_inputs()[0].name | |
outputs = sess.run(None, {input_name: input_array.astype(np.float32)}) | |
## Encuentra la etiqueta con la puntuación más alta | |
label = outputs[0][0][0] | |
score = (outputs[1][0][outputs[0][0][0]]*100) | |
## Devuelve y registra la respuesta | |
response = f"I'm {score:.2f}% sure I see: {label}" | |
logging.info(response) | |
return func.HttpResponse(response) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment