test_predict.py

import requests
import os

# Test configuration
image_path = r"C:\Users\muhammadmaftuh\warisan-digital\ml-service\dataset_batik\batik-parang\1.jpg"
api_url = "https://maftuh-main-batik-classifier.hf.space/predict"

print("\n Testing Batik Classifier API")
print(f"Image: batik-parang\\1.jpg (Expected: batik-parang)\n")
print(" Sending request to API...")

# Send prediction request
with open(image_path, 'rb') as f:
    files = {'image': ('test.jpg', f, 'image/jpeg')}
    response = requests.post(api_url, files=files)

if response.status_code == 200:
    result = response.json()
    print("\n Prediction successful!\n")
    
    print(" Top 5 Predictions:")
    print("=" * 60)
    for i, pred in enumerate(result['predictions'], 1):
        confidence = pred['confidence'] * 100
        bar = "" * int(confidence / 2)
        color = "\033[92m" if i == 1 and confidence > 50 else "\033[0m"
        print(f"{color}  {i}. {pred['class']:<22} {confidence:.2f}% {bar}\033[0m")
    
    print(f"\n Model: {result['model']}")
    print(f" Accuracy: {result['accuracy'] * 100:.1f}%")
else:
    print(f"\n Error: {response.status_code}")
    print(f"Response: {response.text}")