The code appears to involve loading an image, preprocessing it using an unknown function ef
, and passing it through a deep learning model model
to make a prediction. The prediction is then printed, and the preprocessed image is reshaped and displayed using matplotlib
.
image = 'images/train/disgust/299.jpg'
print("original image is of disgust")
img = ef(image)
pred = model.predict(img)
pred_label = label[pred.argmax()]
print("model prediction is ",pred_label)
plt.imshow(img.reshape(48,48),cmap='gray')
import numpy as np
import matplotlib.pyplot as plt
# Image Path
image_path = 'images/train/disgust/299.jpg'
# Load Image
def load_image(image_path):
"""
Loads an image from a file path.
Args:
image_path (str): Path to the image file.
Returns:
np.ndarray: Loaded image.
"""
# TODO: implement image loading using a library like OpenCV
return ef(image_path)
# Process Image
def process_image(img):
"""
Reshapes the image to the required size.
Args:
img (np.ndarray): Input image.
Returns:
np.ndarray: Processed image.
"""
return img.reshape(48, 48)
# Predict Facial Expression
def predict_expression(img):
"""
Uses the model to predict the facial expression.
Args:
img (np.ndarray): Input image.
Returns:
int: Prediction index.
"""
return model.predict(img)
# Get Prediction Label
def get_label(prediction):
"""
Maps the prediction index to a label.
Args:
prediction (int): Prediction index.
Returns:
str: Prediction label.
"""
return label[prediction.argmax()]
# Display Image
def display_image(img):
"""
Displays the image using matplotlib.
Args:
img (np.ndarray): Input image.
"""
plt.imshow(img, cmap='gray')
plt.show()
# Main Function
def main():
# Load Image
img = load_image(image_path)
# Process Image
img = process_image(img)
# Predict Facial Expression
pred = predict_expression(img)
# Get Prediction Label
pred_label = get_label(pred)
# Display Image
display_image(img)
print("Original image is of disgust")
print("Model prediction is", pred_label)
if __name__ == "__main__":
main()
No imports are shown in the provided code, but the following libraries are likely being used:
numpy
(as np
) for numerical operationsmatplotlib.pyplot
(as plt
) for plottingkeras
(or tensorflow.keras
) for deep learning model model
pandas
for accessing data in the label
dictionaryimage
: a string representing the path to a JPEG image fileimg
: the result of calling an unknown function ef
with image
as argumentmodel
: a deep learning model (likely a neural network)label
: a dictionary-like object containing labels for predictionspred
: the result of calling model.predict
with img
as argumentpred_label
: the prediction label corresponding to the highest confidence score in pred
ef
function (unknown implementation).model
for prediction.matplotlib
.