WebMar 25, 2024 · Without those brackets, the i [0]...check is interpreted as a generator comprehension (gives a generator not an iterator) and so just generates the 1st element … WebOct 8, 2024 · 1 Answer. The problem is that you read your image in color mode instead of grayscale ( BGR in OpenCV), but the order of channel is not of essence here (ofc 2352 // …
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WebMar 9, 2024 · 1 Answer Sorted by: 1 If size of image data is 40000 and not equal 1x32x32x3 (One image with width and height, 32 x 32, and RGB format), you reshape it and then got the error. WebAug 29, 2024 · You're trying to reshape a 4096-dimensional image to an image having the shape of (64, 64, 3) -- which denotes an image with RGB color (or BGR color in OpenCV). However, the images being read are grayscale. This means you should not reshape it to (64, 64, 3) but instead to (64, 64, 1). data = img.reshape (1, IMG_SIZE, IMG_SIZE, 1) …
Web6. You can reshape the numpy matrix arrays such that before (a x b x c..n) = after (a x b x c..n). i.e the total elements in the matrix should be same as before, In your case, you can … WebMay 12, 2024 · ValueError: cannot reshape array of size 50176 into shape (1,224,224,3) I am doing image classification and I trained a model and saved a model. When I try to …
WebApr 10, 2024 · But the code fails x_test and x_train with cannot reshape array of size # into shape # ie. for x_train I get the following error: cannot reshape array of size … WebJan 28, 2024 · 1 Answer Sorted by: 3 You probably are trying to predict on an RGB image, while the model requires a grayscale image. What would work is if you do img = img [:,:,0] right after you load the image and then do the remaining process as it is. Share Follow answered Jan 28, 2024 at 5:39 Kalpit 861 8 24
WebSep 23, 2024 · 1 Answer Sorted by: 0 The error is originating from the first line because the total size of the array is not divisible by given reshaping parameters. Here is a toy example:: x_train = train_data.reshape (train_data.shape [0], train_data.shape [1], train_data.shape [2], INPUT_DIMENSION)
WebDec 18, 2024 · You can only reshape an array of one size to another size if the new size has the same number of elements as the old size. In this case, you are attempting to resize … cheryl tiegs fur virginiaWebMar 9, 2024 · Sorted by: 1. If size of image data is 40000 and not equal 1x32x32x3 (One image with width and height, 32 x 32, and RGB format), you reshape it and then got the … flights to port jeffersonWebSep 10, 2024 · This then gives a problem with the reshape: state = np.reshape (state, [1, state_size]) because reshape cannot process a tuple. If you use the gym library 0.12.5, … flights to portland from ontario caWebNov 5, 2024 · from keras.models import load_model from PIL import Image import numpy as np import cv2 model = load_model ('./latest.hdf5') im = Image.open … cheryl tiegs glassesWebMar 17, 2024 · import numpy as np n = 10160 #n = 10083 X = np.arange (n).reshape (1,-1) np.shape (X) X = X.reshape ( [X.shape [0], X.shape [1],1]) X_train_1 = X [:,0:10080,:] … flights to port isaacWeb1 Answer Sorted by: 1 you want array of 300 into 100,100,3. it cannot be because (100*100*3)=30000 and 30000 not equal to 300 you can only reshape if output shape … flights to portland maine american airlinesWebMar 17, 2024 · import numpy as np n = 10160 #n = 10083 X = np.arange (n).reshape (1,-1) np.shape (X) X = X.reshape ( [X.shape [0], X.shape [1],1]) X_train_1 = X [:,0:10080,:] X_train_2 = X [:,10080:10160,:].reshape (1,80) np.shape (X_train_2) If you cannot make sure that X is 10160 long I suggest one of the following solutions: flights to portland from burbank