Created by: hieunm1821

• OS: Ubuntu 18.04
• Python version: 3.6.9
• Paddlelite: 2.6.1

I have downloaded PaddleLite Model from https://paddlemodels.bj.bcebos.com/object_detection/mobile_models/lite/ssdlite_mobilenet_v3_large.tar

My python code for implementing

from paddlelite.lite import *
import numpy as np 
import cv2
config = MobileConfig()
config.set_model_from_file('./ssdlite_mobilenet_v3_large/ssdlite_mobilenet_v3_large.nb')
predictor = create_paddle_predictor(config)
def read_img(im_path, resize_h, resize_w):
	im = cv2.imread(im_path).astype('float32')
	im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
	h, w, _ = im.shape
	im_scale_x = resize_h / float(w)
	im_scale_y = resize_w / float(h)
	out_img = cv2.resize(im, None, None, fx=im_scale_x, fy=im_scale_y, interpolation=cv2.INTER_CUBIC)
	mean = np.array([0.485, 0.456, 0.406]).reshape((1, 1, -1))
	std = np.array([0.229, 0.224, 0.225]).reshape((1, 1, -1))
	out_img = (out_img / 255.0 - mean) / std
	out_img = out_img.transpose((2, 0, 1))
	return out_img

input_tensor = predictor.get_input(0);
height, width = 320, 320
input_tensor.resize([1, 3, height, width])
data = read_img('./kite.jpg', height, width).flatten()
input_tensor.set_float_data(data)

predictor.run()
output_tensor = predictor.get_output(0);
print (output_tensor.shape())

I take the input size 320,320 from https://github.com/PaddlePaddle/PaddleDetection/blob/release/0.3/configs/mobile/README_en.md Error:

 Check failed: output_dims[unk_dim_idx] * capacity == -input_size (-4372 vs. -4374) Invalid shape is given.