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points = [
    ('L-ALam_Apex', '1', 'blue'),
    ('L-ALam_Tip',  '2', 'yellow'),
    ('L-ALam_Touch','3', 'red'),
    ('L-A_eP-Bend', '7', 'orange'),
    ('L-A_eP-End',  '8', 'white'),
    ('L-A_eP-Top',  '6', 'green'),
    ('R-ALam_Apex', '11', 'blue'),
    ('R-ALam_Tip',  '12', 'yellow'),
    ('R-ALam_Touch','13', 'red'),

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def calc_class_ap(lbls, preds, max_dist=30):
    metrics = {}
    for c in classes:
        metrics[c] = [],[],[]
    


    for img_id,pred_row in preds.items():
        lbl_row = lbls[img_id]
        

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# 
# Your previous Plain Text content is preserved below:
# 
# Design a file system.
# File system only deals with directories
# Handle 3 basic commands.
# mkdir - create 1 or more directories (1 level only)
# ls - list files in current directory
# cd - change directory
# pwd - print working directory

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# AUTOGENERATED! DO NOT EDIT! File to edit: 01_metrics.ipynb (unless otherwise specified).

__all__ = ['gaussian', 'create_window', 'SSIM', 'ssim', 'psnr', 'mutual_information', 'nmi', 'metric_fastai',
           'ssim_fastai', 'psnr_fastai', 'nmi_fastai']

# Cell
import torch
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np

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