from sam_encoder import SAMEncoder
from sam_decoder import SAMDecoder
import cv2
import numpy as np
import argparse
import os

if __name__ == "__main__":
    
    parser = argparse.ArgumentParser()
    parser.add_argument("--img_path", "-i", type=str, default="../images/test.jpg", help="input image path")
    parser.add_argument("--output_dir", "-o", type=str, default="./output", help="result path")
    args = parser.parse_args()
    
    encoder = SAMEncoder(f"../onnx/mobile_sam_encoder.onnx")
    decoder = SAMDecoder(f"../onnx/mobile_sam_decoder_slim.onnx")
    
    image = cv2.imread(args.img_path)
    h, w, _ = image.shape
    image_embedding, scale = encoder.encode(image)
    print("Scale:", scale)
    
    point0 = (910, 641)
    point1 = (1488, 607)
    point2 = (579, 704)

    os.makedirs(args.output_dir, exist_ok=True)
    for i, point in enumerate([point0, point1, point2]):
        image_draw = image.copy()
    
        output = decoder.decode(image_embedding[0], point = point,scale = scale)
        idx = output[0].argmax()
    
        image_draw = cv2.circle(image_draw, (int(point[0]), int(point[1])), 10, (0,255,0), -1)
        mask = output[1][:,idx,:,:][0]
        mask_mat = np.zeros((mask.shape[0], mask.shape[1]), dtype=np.uint8)
        mask_mat[mask>0] = 255
        mask_mat = cv2.resize(mask_mat, (max(w, h),max(w, h)),interpolation=cv2.INTER_LINEAR)
        mask_mat = mask_mat[:h, :w]
        cv2.imwrite(f"{args.output_dir}/point_mask_point_{i}.jpg", mask_mat)
        mask_ovlap = np.zeros((mask_mat.shape[0], mask_mat.shape[1], 3), dtype=np.uint8)
        mask_ovlap[mask_mat>0] = [0, 255, 0]
        image_ovlap = cv2.addWeighted(image_draw, 1, mask_ovlap, 0.5, 0)
        cv2.imwrite(f"{args.output_dir}/point_mask_ovlap_point_{i}.jpg", image_ovlap)
    
    
    box0 = (910 - 160, 641 - 430, 380, 940)
    box1 = (479, 482, 191, 518)
    box2 = (1345, 333, 289, 701)
    box3 = (1, 357, 311, 751)
    
    for i, box in enumerate([box0, box1, box2, box3]):
        image_draw = image.copy()
        output = decoder.decode(image_embedding[0], box = box,scale = scale)
        idx = output[0].argmax()

        image_draw = cv2.rectangle(image_draw, (int(box[0]), int(box[1])), (int(box[0]+box[2]), int(box[1]+box[3])), (0,255,0), 2)
        # cv2.imwrite(f"{args.output_dir}/box_image_{i}.jpg", image)

        mask = output[1][:,idx,:,:][0]
        mask_mat = np.zeros((mask.shape[0], mask.shape[1]), dtype=np.uint8)
        mask_mat[mask>0] = 255
        mask_mat = cv2.resize(mask_mat, (max(w, h),max(w, h)),interpolation=cv2.INTER_LINEAR)
        mask_mat = mask_mat[:h, :w]
        cv2.imwrite(f"{args.output_dir}/box_mask_box_{i}.jpg", mask_mat)
        mask_ovlap = np.zeros((mask_mat.shape[0], mask_mat.shape[1], 3), dtype=np.uint8)
        mask_ovlap[mask_mat>0] = [0, 255, 0]
        image_ovlap = cv2.addWeighted(image_draw, 1, mask_ovlap, 0.5, 0)
        cv2.imwrite(f"{args.output_dir}/box_mask_ovlap_box_{i}.jpg", image_ovlap)