Hello guys am workin on Disease Detection from X-Ray Scans Using TinyML, i have gathered a diverse dataset of X-ray images from public medical databases, used images labeled with specific diseases or conditions, such as pneumonia, tuberculosis, or normal/healthy cases, i have also prepared my training script but keep getting an error while training the model
`Traceback (most recent call last):
File ““, line 1, in
File “tensorflow/lite/python/interpreter.py”, line 42, in set_tensor
self._interpreter.SetTensor(self._tensor_index_map[tensor_index], value)
ValueError: Cannot set tensor: Dimension mismatch. Got [1, 128, 128, 3], expected [1, 64, 64, 1]
`

here’s my code
“`python
import tensorflow as tf
from tensorflow.keras import layers, models

model = models.Sequential([
layers.Conv2D(16, (3, 3), activation=’relu’, input_shape=(64, 64, 1)),
layers.MaxPooling2D((2, 2), name=”pool_1″),
layers.Conv2D(32, (3, 3), activation=’relu’, name=”conv_2″),
layers.MaxPooling2D((2, 2), name=”pool_2″),
layers.Flatten(name=”flatten”),
layers.Dense(64, activation=’relu’, name=”dense_1″),
layers.Dense(3, activation=’softmax’, name=”output_layer”)
])
“`