Spaces:
Sleeping
Sleeping
File size: 2,423 Bytes
4f48a4e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | import os
import requests
import io
from PIL import Image
from app import get_image_detector
def download_image(url):
response = requests.get(url, headers={"User-Agent": "Mozilla/5.0"})
response.raise_for_status()
return Image.open(io.BytesIO(response.content)).convert("RGB")
def run_tests():
detector = get_image_detector()
test_cases = [
{
"name": "Real Image - Dog",
"url": "https://images.unsplash.com/photo-1543466835-00a7907e9de1?q=80&w=800&auto=format&fit=crop",
"expected": "REAL"
},
{
"name": "Fake Image - AI Face",
"url": "https://thispersondoesnotexist.com/",
"expected": "FAKE"
},
{
"name": "Real Image - Architecture",
"url": "https://upload.wikimedia.org/wikipedia/commons/4/47/New_york_times_square-terabass.jpg",
"expected": "REAL"
},
{
"name": "Real Image - People",
"url": "https://images.unsplash.com/photo-1517841905240-472988babdf9?ixlib=rb-4.0.3&q=80&w=800&auto=format&fit=crop",
"expected": "REAL"
}
]
print("starting accuracy tests...")
correct = 0
for case in test_cases:
print(f"\nTesting: {case['name']} (Expected: {case['expected']})")
print(f"URL: {case['url']}")
try:
img = download_image(case['url'])
result, _ = detector.predict_with_visuals(img, include_gradcam=False, include_fft=False, include_result_card=False)
label = result['label']
print(f"Result: {label}")
print(f"Fake Prob: {result['fake_prob']:.4f}")
print(f"Real Prob: {result['real_prob']:.4f}")
for model, score in result['scores'].items():
print(f" {model}: {score:.4f}")
if (label == case['expected']) or (label == "FAKE" and case['expected'] == "FAKE") or (label == "REAL" and case['expected'] == "REAL"):
print("[Correct]")
correct += 1
else:
print("[Incorrect]")
except Exception as e:
print(f"[Error] testing {case['name']}: {e}")
print(f"\nAccuracy: {correct}/{len(test_cases)} ({correct/len(test_cases)*100:.1f}%)")
if __name__ == "__main__":
run_tests()
|