🔒 Value error with keras and tensorflow

[dawn crest]

It says the file format is not supported i have tried everything o can
please help me

[gaunt shuttle]

@dawn crest

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[dawn crest]

2024-08-09 11:01:59.442373: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.     
2024-08-09 11:02:13.661594: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.     
Traceback (most recent call last):
  File "c:\Users\Rutwa\Desktop\code\try7\TechVidvan-hand_gesture_detection.py", line 17, in <module>
    model = load_model('mp_hand_gesture')
  File "C:\Users\Rutwa\AppData\Local\Programs\Python\Python310\lib\site-packages\keras\src\saving\saving_api.py", line 204, in load_model
    raise ValueError(
ValueError: File format not supported: filepath=mp_hand_gesture. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(mp_hand_gesture, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
W0000 00:00:1723181567.517049    5864 inference_feedback_manager.cc:114] Feedback manager requires a model with a single signature inference. Disabling support for feedback tensors.
W0000 00:00:1723181567.585863    9252 inference_feedback_manager.cc:114] Feedback manager requires a model with a single signature inference. Disabling support for feedback tensors.

this is the error

[gaunt shuttle]

Hey @dawn crest!

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You can **edit your original message** to correct your code block.

[dawn crest]

# TechVidvan hand Gesture Recognizer

# import necessary packages

import cv2
import numpy as np
import mediapipe as mp
import tensorflow as tf
from tensorflow.keras.models import load_model

# initialize mediapipe
mpHands = mp.solutions.hands
hands = mpHands.Hands(max_num_hands=1, min_detection_confidence=0.7)
mpDraw = mp.solutions.drawing_utils

# Load the gesture recognizer model
model = load_model('mp_hand_gesture')

# Load class names
f = open('gesture.names', 'r')
classNames = f.read().split('\n')
f.close()
print(classNames)


# Initialize the webcam
cap = cv2.VideoCapture(0)

while True:
    # Read each frame from the webcam
    _, frame = cap.read()

    x, y, c = frame.shape

    # Flip the frame vertically
    frame = cv2.flip(frame, 1)
    framergb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    # Get hand landmark prediction
    result = hands.process(framergb)

    # print(result)
    
    className = ''

    # post process the result
    if result.multi_hand_landmarks:
        landmarks = []
        for handslms in result.multi_hand_landmarks:
            for lm in handslms.landmark:
                # print(id, lm)
                lmx = int(lm.x * x)
                lmy = int(lm.y * y)

                landmarks.append([lmx, lmy])

            # Drawing landmarks on frames
            mpDraw.draw_landmarks(frame, handslms, mpHands.HAND_CONNECTIONS)

            # Predict gesture
            prediction = model.predict([landmarks])
            # print(prediction)
            classID = np.argmax(prediction)
            className = classNames[classID]

    # show the prediction on the frame
    cv2.putText(frame, className, (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 
                   1, (0,0,255), 2, cv2.LINE_AA)

    # Show the final output
    cv2.imshow("Output", frame) 

    if cv2.waitKey(1) == ord('q'):
        break

# release the webcam and destroy all active windows
cap.release()

cv2.destroyAllWindows()

thisis the code

[gaunt shuttle]

@dawn crest

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