Görüntü sınıflandırma istemci uygulaması oluşturma
Görüntü sınıflandırma modelini eğitdikten sonra, sınıflandırılacak yeni görüntüler gönderen bir istemci uygulaması geliştirmek için Azure AI Özel Görüntü İşleme SDK'sını kullanabilirsiniz.
from msrest.authentication import ApiKeyCredentials
from azure.cognitiveservices.vision.customvision.prediction import CustomVisionPredictionClient
# Authenticate a client for the prediction API
credentials = ApiKeyCredentials(in_headers={"Prediction-key": "<YOUR_PREDICTION_RESOURCE_KEY>"})
prediction_client = CustomVisionPredictionClient(endpoint="<YOUR_PREDICTION_RESOURCE_ENDPOINT>",
credentials=credentials)
# Get classification predictions for an image
image_data = open("<PATH_TO_IMAGE_FILE>"), "rb").read()
results = prediction_client.classify_image("<YOUR_PROJECT_ID>",
"<YOUR_PUBLISHED_MODEL_NAME>",
image_data)
# Process predictions
for prediction in results.predictions:
if prediction.probability > 0.5:
print(image, ': {} ({:.0%})'.format(prediction.tag_name, prediction.probability))
using System;
using System.IO;
using Microsoft.Azure.CognitiveServices.Vision.CustomVision.Prediction;
// Authenticate a client for the prediction API
CustomVisionPredictionClient prediction_client = new CustomVisionPredictionClient(new ApiKeyServiceClientCredentials("<YOUR_PREDICTION_RESOURCE_KEY>"))
{
Endpoint = "<YOUR_PREDICTION_RESOURCE_ENDPOINT>"
};
// Get classification predictions for an image
MemoryStream image_data = new MemoryStream(File.ReadAllBytes("<PATH_TO_IMAGE_FILE>"));
var result = prediction_client.ClassifyImage("<YOUR_PROJECT_ID>",
"<YOUR_PUBLISHED_MODEL_NAME>",
image_data);
// Process predictions
foreach (var prediction in result.Predictions)
{
if (prediction.Probability > 0.5)
{
Console.WriteLine($"{prediction.TagName} ({prediction.Probability})");
}
}