vis.py

import argparse
import json
import tqdm
import cv2
import os
import numpy as np
from pycocotools import mask as mask_utils
import random
from PIL import Image


EVALMODE = "test"


def blend_mask(input_img, binary_mask, alpha=0.3):
    mask_image = np.zeros(input_img.shape, np.uint8)
    mask_image[:, :, 0] = 255
    mask_image[:, :, 1] = 165
    mask_image[:, :, 2] = 0

    mask_image = mask_image * np.repeat(binary_mask[:, :, np.newaxis], 3, axis=2)
    blend_image = input_img[:, :, :].copy()
    pos_idx = binary_mask > 0
    for ind in range(input_img.ndim):
        ch_img1 = input_img[:, :, ind]
        ch_img2 = mask_image[:, :, ind]
        ch_img3 = blend_image[:, :, ind]
        ch_img3[pos_idx] = alpha * ch_img1[pos_idx] + (1 - alpha) * ch_img2[pos_idx]
        blend_image[:, :, ind] = ch_img3
    return blend_image


def upsample_mask(mask, frame):
    H, W = frame.shape[:2]
    mH, mW = mask.shape[:2]

    if W > H:
        ratio = mW / W
        h = H * ratio
        diff = int((mH - h) // 2)
        if diff == 0:
            mask = mask
        else:
            mask = mask[diff:-diff]
    else:
        ratio = mH / H
        w = W * ratio
        diff = int((mW - w) // 2)
        if diff == 0:
            mask = mask
        else:
            mask = mask[:, diff:-diff]

    mask = cv2.resize(mask, (W, H))
    return mask


def downsample(mask, frame):
    H, W = frame.shape[:2]
    mH, mW = mask.shape[:2]

    mask = cv2.resize(mask, (W, H))
    return mask


#datapath /datasegswap
#inference_path /inference_xmem_ego_last/coco
#output /vis_piano
#--show_gt要加上
if __name__ == "__main__":


   
    out_path = "/home/yuqian_fu/Projects/sam2/predicted_mask"
    


        
    
    frame = cv2.imread(
        "/data/work-gcp-europe-west4-a/yuqian_fu/Ego/multi_view_data_2/multi_vew_data_3/000001-color.jpg"
    )
    mask = Image.open("/data/work-gcp-europe-west4-a/yuqian_fu/Ego/multi_view_data_2/mask/000001-label.png")
    mask = np.array(mask)
    mask = cv2.resize(mask, (frame.shape[1], frame.shape[0]))

    
    mask = upsample_mask(mask, frame)
    out = blend_mask(frame, mask)
    

    cv2.imwrite(
        f"{out_path}/cor_0.jpg",
        out,
    )