Simple Testing Image Classification

simpleImageClassifier

imagePath = "test.jpg"

# Replace this with the path to your image
image = Image.open(imagePath).convert("RGB")

# resizing the image to be at least 224x224 and then cropping from the center
size = (224, 224)
# image = ImageOps.fit(image, size, resample=Image.BICUBIC)
image = image.resize(size, resample=Image.BICUBIC)

# turn the image into a numpy array
image_array = np.asarray(image)

# Normalize the image
normalized_image_array = (image_array.astype(np.float32) / 127.5) - 1

# Load the image into the array
data[0] = normalized_image_array

# Predicts the model
prediction = model.predict(data)
index = np.argmax(prediction)
class_name = class_names[index]
confidence_score = prediction[0][index]

# Print prediction and confidence score
print("Class:", class_name[2:], end="")
print("Confidence Score:", confidence_score)