Created by: wang-kangkang

为了便于我后边的改写和模块级优化，我将tools/infer.py进行了精简。代码主体已经完成，但有某个未知的小细节没处理对，导致结果不正确。希望能帮忙看下我哪里没写对：

from ppdet.modeling.backbones.mobilenet import MobileNet
from ppdet.modeling.anchor_heads.yolo_head import YOLOv3Head
from ppdet.modeling.architectures.yolo import YOLOv3
import paddle.fluid as fluid
import numpy as np
import cv2

if __name__=="__main__":
    #准备输入数据
    image = cv2.imread('demo/orange_71.jpg')
    image = cv2.resize(image, dsize=(512, 512))
    image = image.transpose((2,0,1))
    image = image[np.newaxis, :, :, :].astype(np.float32)
    image_size = np.array([512, 512])
    image_size = image_size[np.newaxis, :]
    
    #定义设备和program
    place = fluid.core.CPUPlace()
    exe = fluid.Executor(place)
    startup_program = fluid.Program()
    inference_program = fluid.Program()

    #搭建网络结构
    backbone = MobileNet()
    head = YOLOv3Head(num_classes=3)
    model = YOLOv3(backbone = backbone, yolo_head=head)
    with fluid.program_guard(inference_program, startup_program):
        data = fluid.layers.data(name = 'image', shape=[-1, 3, 512, 512], dtype='float32')
        im_size = fluid.layers.data(name = 'im_size', shape=[-1, 2], dtype='float32')
        test_fetches = model.test({'image':data, 'im_size':im_size})
    inference_program = inference_program.clone(for_test=True)

    #加载预训练模型
    fluid.io.load_persistables(executor=exe, dirname='C:\\Users\\Administrator\\.cache\\paddle\\weights\\yolov3_mobilenet_v1_fruit', main_program = inference_program)

    #前项预测并输出结果
    output = exe.run(inference_program, fetch_list = [test_fetches['bbox']], feed={'image': image, 'im_size':image_size}, return_numpy=False)
    output = np.array(output[0])
    print(output)
    #cv2.rectangle(...)
    #cv2.putText(...)
    #cv2.imwrite(...)