| 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) |
| |
|
|
| 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) |
| |
