How to use MediaPipe pose to make detections?

Question

I want to use MediaPipe for a project with keypoints detection but after writing a code that applies the model to a specific video, I get a RunTime error that I don't know how to correct.Here is the code

cap = cv2.VideoCapture("FitnessBasic/squat/data/000076.mp4")

## Setup mediapipe instance
with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
    while cap.isOpened():
        ret, frame = cap.read()
        
        # Recolor image to RGB
        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        image.flags.writeable = False
      
        # Make detection
        results = pose.process(image)
    
        # Recolor back to BGR
        image.flags.writeable = True
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
        
        # Render detections
        mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
            mp_drawing.DrawingSpec(color=(245,117,66), thickness=2, circle_radius=2), 
            mp_drawing.DrawingSpec(color=(245,66,230), thickness=2, circle_radius=2))               

    cap.release()

And here is the error I encounter

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
Cell In[8], line 3
      1 cap = cv2.VideoCapture("FitnessBasic/squat/data/000076.mp4")
      2 ## Setup mediapipe instance
----> 3 with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
      4     while cap.isOpened():
      5         ret, frame = cap.read()

File ~/anaconda3/lib/python3.11/site-packages/mediapipe/python/solutions/pose.py:146, in Pose.__init__(self, static_image_mode, model_complexity, smooth_landmarks, enable_segmentation, smooth_segmentation, min_detection_confidence, min_tracking_confidence)
    122 """Initializes a MediaPipe Pose object.
    123 
    124 Args:
   (...)
    143     https://solutions.mediapipe.dev/pose#min_tracking_confidence.
    144 """
    145 _download_oss_pose_landmark_model(model_complexity)
--> 146 super().__init__(
    147     binary_graph_path=_BINARYPB_FILE_PATH,
    148     side_inputs={
    149         'model_complexity': model_complexity,
    150         'smooth_landmarks': smooth_landmarks and not static_image_mode,
    151         'enable_segmentation': enable_segmentation,
    152         'smooth_segmentation':
    153             smooth_segmentation and not static_image_mode,
...
ConstantSidePacketCalculator: ; RET_CHECK failure (mediapipe/calculators/core/constant_side_packet_calculator.cc:64) (cc->OutputSidePackets().NumEntries(kPacketTag))==(options.packet_size())Number of output side packets has to be same as number of packets configured in options.
ConstantSidePacketCalculator: ; RET_CHECK failure (mediapipe/calculators/core/constant_side_packet_calculator.cc:64) (cc->OutputSidePackets().NumEntries(kPacketTag))==(options.packet_size())Number of output side packets has to be same as number of packets configured in options.
SplitTensorVectorCalculator: The number of output streams should match the number of ranges specified in the CalculatorOptions.
SplitNormalizedLandmarkListCalculator: The number of output streams should match the number of ranges specified in the CalculatorOptions.
SplitLandmarkListCalculator: The number of output streams should match the number of ranges specified in the CalculatorOptions.

I tried updating mediapipe

pip install --upgrade mediapipe

And I also tried simplifying the initialization

with mp_pose.Pose() as pose:

But none of those worked.