Question

我正在尝试在自己的数据集上训练SSD，并且正在使用以下keras实现-

https://github.com/pierluigiferrari/ssd_keras

尝试运行以下代码时，我不断收到以下错误“ ValueError：尺寸必须相等，但对于带有输入形状的'conv4_3_norm / mul'（op：'Mul'），尺寸应为512和38：[?, 38,38,512]，[38]。“

我试图更改输入图像的大小，但似乎无济于事。

Pip安装列表（我认为很重要）

opencv-python == 4.1.2.30
Keras == 2.0.3
tensorflow-gpu == 1.14.0

from keras import backend as K
from keras.models import load_model
from keras.optimizers import Adam
from scipy.misc import imread
import numpy as np
from matplotlib import pyplot as plt

from models.keras_ssd300 import ssd_300
from keras_loss_function.keras_ssd_loss import SSDLoss
from keras_layers.keras_layer_AnchorBoxes import AnchorBoxes
from keras_layers.keras_layer_DecodeDetections import DecodeDetections
from keras_layers.keras_layer_DecodeDetectionsFast import DecodeDetectionsFast
from keras_layers.keras_layer_L2Normalization import L2Normalization
from data_generator.object_detection_2d_data_generator import DataGenerator
from eval_utils.average_precision_evaluator import Evaluator

img_height = 300
img_width = 300
n_classes = 20
model_mode = 'inference'

K.clear_session() # Clear previous models from memory.

model = ssd_300(image_size=(img_height, img_width, 3),
                n_classes=n_classes,
                mode=model_mode,
                l2_regularization=0.0005,
                scales=[0.1, 0.2, 0.37, 0.54, 0.71, 0.88, 1.05], # The scales for MS COCO [0.07, 0.15, 0.33, 0.51, 0.69, 0.87, 1.05]
                aspect_ratios_per_layer=[[1.0, 2.0, 0.5],
                                         [1.0, 2.0, 0.5, 3.0, 1.0/3.0],
                                         [1.0, 2.0, 0.5, 3.0, 1.0/3.0],
                                         [1.0, 2.0, 0.5, 3.0, 1.0/3.0],
                                         [1.0, 2.0, 0.5],
                                         [1.0, 2.0, 0.5]],
                two_boxes_for_ar1=True,
                steps=[8, 16, 32, 64, 100, 300],
                offsets=[0.5, 0.5, 0.5, 0.5, 0.5, 0.5],
                clip_boxes=False,
                variances=[0.1, 0.1, 0.2, 0.2],
                normalize_coords=True,
                subtract_mean=[123, 117, 104],
                swap_channels=[2, 1, 0],
                confidence_thresh=0.01,
                iou_threshold=0.45,
                top_k=200,
                nms_max_output_size=400)

无法创建Keras SSD模型

0 个答案: