update

inf_demo.py

@@ -0,0 +1,67 @@
+import os
+import argparse
+import cv2
+import readline
+import tqdm
+import time
+
+import torch
+from torch.utils.data import DataLoader
+from PIL import Image
+
+# from smplerx.main.inference import Inferer
+from main.inference import SmplerxData, Inferer
+
+
+import pdb
+
+
+def inference(args):
+
+    # load model
+    num_gpus = 1 if torch.cuda.is_available() else -1
+    inferer = Inferer(args.pretrained_model, num_gpus)
+
+    # test annotations
+    annotations = [
+        {'image_path': '/home/weichen/wc_workspace/laoyouji/frames/Season_1/S01E01/frame025000.jpg', 'bbox': [0, 0, 1000, 1000]},
+        {'image_path': '/home/weichen/wc_workspace/laoyouji/frames/Season_1/S01E01/frame026000.jpg', 'bbox': [0, 0, 1000, 1000]}
+    ]
+
+    annotations = annotations*500
+    anno_len = len(annotations)
+    
+    start_time = time.time()
+    batch_size = 1
+    
+    dataset = SmplerxData(annotations=annotations)
+    dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=False, num_workers=4)
+
+    preproces_time = time.time()
+
+    for batch in tqdm.tqdm(dataloader):
+
+        smplx_pred, meta, mesh = inferer.batch_infer_given_bbox(batch['image'], batch['bbox'])
+
+    end_time = time.time()
+
+    # print report, time in seconds
+    print(f'Instance number: {anno_len}, Batch size: {batch_size}')
+    print(f'Preprocess time: {preproces_time-start_time:02f}, FPS: {anno_len/(preproces_time-start_time):02f}')
+    print(f'Inference time: {end_time-preproces_time:02f}, FPS: {anno_len/(end_time-preproces_time):02f}')
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument('--in_threshold', type=float, default=0.5)
+    parser.add_argument('--pretrained_model', type=str, default='smpler_x_h32')
+
+    args = parser.parse_args()
+
+    inference(args)
+
+
+
+

main/inference.py

@@ -18,9 +18,9 @@ CUR_DIR = osp.dirname(os.path.abspath(__file__))
 sys.path.insert(0, osp.join(CUR_DIR, '..', 'main'))
 sys.path.insert(0, osp.join(CUR_DIR , '..', 'common'))
 from config import cfg, model_path_dict
-from ..common.base import Demoer
-from ..common.utils.preprocessing import process_bbox, generate_patch_image
-from ..common.utils.human_models import smpl_x
+from base import Demoer
+from utils.preprocessing import process_bbox, generate_patch_image
+from utils.human_models import smpl_x
 
 class SmplerxData(Dataset):
     def __init__(self, annotations):
@@ -39,7 +39,6 @@ class SmplerxData(Dataset):
 
         # prepare input image
         transform = transforms.ToTensor()
-        vis_img = image.copy()
         original_img_height, original_img_width = image.shape[:2]
         bbox = process_bbox(bbox, original_img_width, original_img_height)
         img, img2bb_trans, bb2img_trans = generate_patch_image(image, bbox, 1.0, 0.0, False, (512, 384))