sandeep-25

Hi, can you please give the exact formula or method that you have used in your code to set the values of train_num_array.

X_result=np.zeros((labels.shape[0]*labels.shape[1],3)) num_class=labels.max() X_result = np.zeros((labels.shape[0]*labels.shape[1],3)) for i in range(0,num_class): X_result[np.where(labels==i),0] = palette[i,0] X_result[np.where(labels==i),1] = palette[i,1] X_result[np.where(labels==i),2] = palette[i,2] I repeated the experiment as per your comment but I am not...

Can anyone send the modified code to [email protected] for the error- Negative dimension size caused by subtracting 3 from 1 for 'conv_1/Conv2D' (op: 'Conv2D') with input shapes: [100,1,1,220], [3,3,220,500].