Empresas
Empregos
  • Sobre nós
  • Soluções
    • Publicação de vagas
      Publique sua vaga e receba candidatos qualificados em 48h.
    • Avaliações de candidatos
      Mais de 500 testes técnicos e psicológicos, mais anti-fraude.
    • Headhunting
      Busca executiva personalizada do início ao fim.
    • Folha de Pagamento + EOR
      Dispersão de folha e EOR em mais de 15 países da LATAM.
  • Preços
  • Empregos

0

126
Visualizações
Tensorflow Serving keeps returning the same output

So, I'm following this tutorial: https://www.youtube.com/watch?v=t6NI0u_lgNo&t=1826s and right after the tensorflow serving part I had been testing my fastapi API code which looks like this:

from fastapi import FastAPI, File, UploadFile
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
import numpy as np
from io import BytesIO
from PIL import Image
import tensorflow as tf
import os
import requests

os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
app = FastAPI()

endpoint = "http://localhost:8501/v1/models/plant_model:predict"

CLASS_NAMES = ['Potato___Early_blight',
               'Potato___Late_blight',
               'Potato___healthy',
               'Tomato_Early_blight',
               'Tomato_Late_blight',
               'Tomato_healthy']


@app.get("/ping")
async def ping():
    return "Hello, I am alive"


def read_file_as_image(data) -> np.ndarray:
    image = np.array(Image.open(BytesIO(data)))
    return image


@app.post("/predict")
async def predict(
    file: UploadFile = File(...)
):
    image = read_file_as_image(await file.read())
    img_batch = np.expand_dims(image, 0)

    json_data = {
        "instances": img_batch.tolist()
    }

    response = requests.post(endpoint, json=json_data)
    prediction = np.array(response.json()["predictions"][0])

    predicted_class = CLASS_NAMES[np.argmax(prediction[0])]
    confidence = np.max(prediction[0])

    return {
        'class': predicted_class,
        'confidence': float(confidence)
    }

if __name__ == "__main__":
    uvicorn.run(app, host='localhost', port=8000)

By the way I'm using Ubuntu Ubuntu 20.04.

and I'm passing the image of a 255x255 leaf to it. (my model is made to classify different kinds of diseases for different kinds of vegetable leaves)

But, for some reason it always gives me this same false output:

    "class": "Potato___Early_blight",
    "confidence": 0.374938548
}

I also tried it with another leaf image but it's still the same just with a different confidence:

    "class": "Potato___Early_blight",
    "confidence": 1.21042137e-06

I can't post images here because my rank is too low

and here is the link to the AI google colab notebook I made for the AI:https://colab.research.google.com/drive/1i2v_RbZ8lI-e0joE-qBxym6_6xF5rR0g?usp=sharing

So, what am I doing wrong? I have checked other answers but they go into the specifics of the code instead of a general answer.

over 4 years ago · Santiago Trujillo
Responde à pergunta
Encontrar trabalhos remotos

Descubra a nova forma de encontrar um emprego!

melhores empregos
Principais categorias de trabalho
Empresas
Postar vaga Preços Comercial
Jurídico
Termos e Condições Política de privacidade
© 2026 PeakU Inc. All Rights Reserved.
Andres GPT
Recomende algumas ofertas para mim
Preciso de ajuda