Load Checkpoint And Evaluate Single Image With Tensorflow Dnn

For research at university I am examining the oxford 17 flowers alexnet example. The example uses the API tflearn based on tensorflow. Training is working very well on my GPU, reac

Solution 1:

for save: model.save('name.tflearn')

for load: model.load('name.tflearn')

and for testing in loop just load the model and follow following code

files_path = '/your/test/images/directory/path'
img_files_path = os.path.join(files_path, '*.jpg')
img_files = sorted(glob(img_files_path))

for f in img_files:
    try:
        img = Image.open(f).convert('RGB')
        img = ImageOps.fit(img, ((64, 64)), Image.ANTIALIAS)

        img_arr = np.array(img)
        img_arr = img_arr.reshape(-1, 64, 64, 3).astype("float")

        pred = model.predict(img_arr)
        print(" %s" % pred[0])

    except:
        continue