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from main import *
import cv2
import time
model_path = "raf-db-model_best.pth"
if torch.backends.mps.is_available():
device = "mps"
elif torch.cuda.is_available():
device = "cuda"
else:
device = "cpu"
model = pyramid_trans_expr2(img_size=224, num_classes=7)
model = torch.nn.DataParallel(model)
model = model.to(device)
currtime = time.strftime("%H:%M:%S")
print(currtime)
def main():
if model_path is not None:
if os.path.isfile(model_path):
print("=> loading checkpoint '{}'".format(model_path))
checkpoint = torch.load(model_path, map_location=device)
best_acc = checkpoint["best_acc"]
best_acc = best_acc.to()
print(f"best_acc:{best_acc}")
model.load_state_dict(checkpoint["state_dict"])
print(
"=> loaded checkpoint '{}' (epoch {})".format(
model_path, checkpoint["epoch"]
)
)
else:
print("=> no checkpoint found at '{}'".format(model_path))
imagecapture(model)
return
def imagecapture(model):
currtimeimg = time.strftime("%H:%M:%S")
cap = cv2.VideoCapture(0)
if not cap.isOpened():
print("Error: Could not open webcam.")
exit()
face_cascade = cv2.CascadeClassifier(
cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
)
start_time = None
capturing = False
while True:
from prediction import predict
ret, frame = cap.read()
if not ret:
print("Error: Could not read frame.")
break
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(
gray, scaleFactor=1.3, minNeighbors=5, minSize=(30, 30)
)
# Display the frame
cv2.imshow("Webcam", frame)
# If faces are detected, start the timer
if len(faces) > 0:
print(f"[!]Face detected at {currtimeimg}")
face_region = frame[
faces[0][1] : faces[0][1] + faces[0][3],
faces[0][0] : faces[0][0] + faces[0][2],
] # Crop the face region
face_pil_image = Image.fromarray(
cv2.cvtColor(face_region, cv2.COLOR_BGR2RGB)
) # Convert to PIL image
print("[!]Start Expressions")
print(f"-->Prediction starting at {currtimeimg}")
predictions = predict(model, image_path=face_pil_image)
print(f"-->Done prediction at {currtimeimg}")
# Reset capturing
capturing = False
# Break the loop if the 'q' key is pressed
if cv2.waitKey(1) & 0xFF == ord("q"):
break
# Release the webcam and close the OpenCV window
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
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