helper.py

import os
import sys
import matplotlib.pyplot as plt
import numpy as np
import utils.misc as misc
import torch.nn.functional as F

def compute_iou(preds, target):
    assert target.shape[1] == 1, 'only support one mask per image now'
    if(preds.shape[2]!=target.shape[2] or preds.shape[3]!=target.shape[3]):
        postprocess_preds = F.interpolate(preds, size=target.size()[2:], mode='bilinear', align_corners=False)
    else:
        postprocess_preds = preds
    iou = 0
    for i in range(0,len(preds)): # len(preds) == 1
        iou = iou + misc.mask_iou(postprocess_preds[i],target[i])
        # print the number of 255 in target
    #     print('target:', target[i].shape, (target[i]/255).sum())
    #     print('compute_iou:', iou)
    # print('iou, len(preds):', iou, len(preds))
    # print('return:', iou / len(preds))
    return iou / len(preds)

def compute_boundary_iou(preds, target):
    assert target.shape[1] == 1, 'only support one mask per image now'
    if(preds.shape[2]!=target.shape[2] or preds.shape[3]!=target.shape[3]):
        postprocess_preds = F.interpolate(preds, size=target.size()[2:], mode='bilinear', align_corners=False)
    else:
        postprocess_preds = preds
    iou = 0
    for i in range(0,len(preds)):
        iou = iou + misc.boundary_iou(target[i],postprocess_preds[i])
    return iou / len(preds)

def show_anns(masks, input_point, input_box, input_label, filename, image, ious, boundary_ious):
    if len(masks) == 0:
        return

    for i, (mask, iou, biou) in enumerate(zip(masks, ious, boundary_ious)):
        plt.figure(figsize=(10,10))
        plt.imshow(image)
        show_mask(mask, plt.gca())
        if input_box is not None:
            show_box(input_box, plt.gca())
        if (input_point is not None) and (input_label is not None): 
            show_points(input_point, input_label, plt.gca())

        plt.axis('off')
        plt.savefig(filename+'_'+str(i)+'.png',bbox_inches='tight',pad_inches=-0.1)
        plt.close()

def show_mask(mask, ax, random_color=False):
    if random_color:
        color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)
    else:
        color = np.array([30/255, 144/255, 255/255, 0.6])
    h, w = mask.shape[-2:]
    mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)
    ax.imshow(mask_image)
    
def show_points(coords, labels, ax, marker_size=375):
    pos_points = coords[labels==1]
    neg_points = coords[labels==0]
    ax.scatter(pos_points[:, 0], pos_points[:, 1], color='green', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)
    ax.scatter(neg_points[:, 0], neg_points[:, 1], color='red', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)   
    
def show_box(box, ax):
    x0, y0 = box[0], box[1]
    w, h = box[2] - box[0], box[3] - box[1]
    ax.add_patch(plt.Rectangle((x0, y0), w, h, edgecolor='green', facecolor=(0,0,0,0), lw=2))