I have done this basic project with Anaconda notebook. Everything runs fine, but every prediction with my own digit picture is wrong. I am using the MNIST Set for digital numbers and I am trying to paint my own digit with black background and white painting. But every prediction is wrong. Could one see what´s missing in the code? # Install TensorFlow import tensorflow as tf # Import matplotlib library import matplotlib.pyplot as plt #Import numpy import numpy as np #import cv import cv2 #Dataset mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation='softmax')]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) model.fit(x_train, y_train, epochs=5) print("Evaluierung"); model.evaluate(x_test, y_test) plt.imshow(x_train[1], cmap="gray") # Import the image plt.show() # Plot the image predictions = model.predict([x_train]) # Make prediction, works perfect print(np.argmax(predictions[1])) # Print out the number, works perfect # my own picture, black background, white color, 28 px * 28 px in size img = cv2.imread("bild1.png", cv2.IMREAD_GRAYSCALE) plt.imshow(img) # Import the image plt.show() # Plot the image cv2.imshow("image",img) cv2.waitKey(2000) img = img/255.0 img = img.reshape(1,28,28) pred = model.predict_classes(img) print("Prediction: ", pred) Every prediction from the training and test data are correct, my own pictures are ALL wrong with NO error code! It would be great if you could help me Continue reading...
