我是深度學習和 TensorFlow/Keras 的新手，所以我無法理解為什么我在嘗試擬合模型以將圖像分類為“狗”或“貓”時拋出錯誤。第一個代碼塊涉及創建和保存模型（使用 pickle），第二個代碼塊是訓練實際卷積網絡的部分。下載圖像數據庫，保存到文件目錄，編寫模型訓練分類器。代碼如下：import numpy as npimport matplotlib.pyplot as pltimport osimport cv2DATADIR = "Pictures\\kagglecatsanddogs_3367a\\PetImages"?#Workspace directory changed for postingCATEGORIES = ["Dog", "Cat"]#Iterate between all photos of dogs and catsfor category in CATEGORIES:? ? path = os.path.join(DATADIR, category) #path to cats or dogs dir? ? for img in os.listdir(path):? ? ? ? img_array = cv2.imread(os.path.join(path, img), cv2.IMREAD_GRAYSCALE) #Converts to grayscale, does not need color in this specific instance)? ? ? ? plt.imshow(img_array, cmap = "gray")? ? ? ? break? ? break#Print image dimensionsprint(img_array.shape)#All the images are different-shaped photos, so they must be normalized#Everything must be made the same shape#Decide on the image size you want to go withIMG_SIZE = 180new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))training_data = []def create_training_data(): #With goal of iterating through everything and building the dataset? ? for category in CATEGORIES:? ? ? ? path = os.path.join(DATADIR, category) #path to cats or dogs dir? ? ? ? class_num = CATEGORIES.index(category)? ? ? ? for img in os.listdir(path):? ? ? ? ? ? try:? ? ? ? ? ? ? ? img_array = cv2.imread(os.path.join(path, img), cv2.IMREAD_GRAYSCALE) #Converts to grayscale, does not need color in this specific instance)? ? ? ? ? ? ? ? new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))? ? ? ? ? ? ? ? training_data.append([new_array, class_num])? ? ? ? ? ? except Exception as e:? ? ? ? ? ? ? ? pass
4 回答
青春有我
TA貢獻1784條經驗 獲得超8個贊
您應該對 y 的 numpy 數組進行轉換過程，而不僅僅是 X。
X = []
y = []
for features,label in training_data:
X.append(features)
y.append(label)
print(X[0].reshape(-1, IMG_SIZE, IMG_SIZE, 1))
X = np.array(X).reshape(-1, IMG_SIZE, IMG_SIZE, 1)
y = np.array(y)
翻翻過去那場雪
TA貢獻2065條經驗 獲得超14個贊
import numpy as np
X = np.array(X).reshape(-1,IMG_SIZE,IMG_SIZE,1)
y = np.array(y)
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Conv2D, MaxPooling2D
import pickle
. . .
并繼續。我也遇到過同樣的問題，但它在將數據加載到 NumPy 數組后起作用，正如我通過添加定義 X 和 y 的額外行所提到的那樣。
繁花不似錦
TA貢獻1851條經驗 獲得超4個贊
只需添加
y = np.array(y)
在您之后的最后一個程序中
#Load models generated in previous tutorial
x = pickle.load(open("x.pickle", "rb"))
y = pickle.load(open("y.pickle", "rb"))
y = np.array(y)
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