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rsokl avatar rsokl commented on July 17, 2024

An attempt to clean up OP's code-snippet.

def extract_random_LAF(data, max_rot = math.pi, max_tilt = 1.0, crop_size = 32): 
    st = int((data.size(2) - crop_size)/2) 
    fin = st + crop_size 
    if type(max_rot) is float: 
        rot_LAFs, inv_rotmat = get_random_rotation_LAFs(data, max_rot) 
    else: 
        rot_LAFs = max_rot 
        inv_rotmat = None 
    aff_LAFs, inv_TA = get_random_norm_affine_LAFs(data, max_tilt); 
    aff_LAFs[:,0:2,0:2] = torch.bmm(rot_LAFs[:,0:2,0:2],aff_LAFs[:,0:2,0:2])  # pdb.set_trace() 
    data_aff = extract_patches(data, aff_LAFs, PS = data.size(2)) 
    data_aff = extract_patches(data_aff, rot_LAFs, PS = data.size(2))   
    data_affcrop = data_aff[:,:, st:fin, st:fin].contiguous() 
    return data_affcrop, data_aff, rot_LAFs,inv_rotmat,inv_TA 

@ducha-aiki have you looked into this issue?

from affnet.

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