import tensorflow as tf
import numpy as np
import pickle, os, cv2
tf.logging.set_verbosity(tf.logging.INFO)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
def get_image_size():
img = cv2.imread('gestures/0/100.jpg', 0)
return img.shape
def get_num_of_classes():
return len(os.listdir('gestures/'))
image_x, image_y = get_image_size()
def cnn_model_fn(features, labels, mode):
input_layer = tf.reshape(features["x"], [-1, image_x, image_y, 1], name="input")
conv1 = tf.layers.conv2d(
inputs=input_layer,
filters=16,
kernel_size=[2, 2],
padding="same",
activation=tf.nn.relu,
name="conv1")
print("conv1",conv1.shape)
pool1 = tf.layers.max_pooling2d(inputs=conv1, pool_size=[2, 2], strides=2, name="pool1")
print("pool1",pool1.shape)
conv2 = tf.layers.conv2d(
inputs=pool1,
filters=32,
kernel_size=[5, 5],
padding="same",
activation=tf.nn.relu,
name="conv2")
print("conv2",conv2.shape)
pool2 = tf.layers.max_pooling2d(inputs=conv2, pool_size=[5, 5], strides=5, name="pool2")
print("pool2",pool2.shape)
conv3 = tf.layers.conv2d(
inputs=pool2,
filters=64,
kernel_size=[5, 5],
padding="same",
activation=tf.nn.relu,
name="conv3")
print("conv3",conv3.shape)
# Dense Layer
flat = tf.reshape(conv3, [-1, 5*5*64], name="flat")
print(flat.shape)
dense = tf.layers.dense(inputs=flat, units=128, activation=tf.nn.relu, name="dense")
print(dense.shape)
dropout = tf.layers.dropout(inputs=dense, rate=0.2, training=mode == tf.estimator.ModeKeys.TRAIN, name="dropout")
# Logits Layer
num_of_classes = get_num_of_classes()
logits = tf.layers.dense(inputs=dropout, units=num_of_classes, name="logits")
output_class = tf.argmax(input=logits, axis=1, name="output_class")
output_probab = tf.nn.softmax(logits, name="softmax_tensor")
predictions = {"classes": tf.argmax(input=logits, axis=1), "probabilities": tf.nn.softmax(logits, name="softmax_tensor")}
#tf.Print(tf.nn.softmax(logits, name="softmax_tensor"), [tf.nn.softmax(logits, name="softmax_tensor")])
if mode == tf.estimator.ModeKeys.PREDICT:
return tf.estimator.EstimatorSpec(mode=mode, predictions=predictions)
# Calculate Loss (for both TRAIN and EVAL modes)
onehot_labels = tf.one_hot(indices=tf.cast(labels, tf.int32), depth=num_of_classes)
loss = tf.losses.softmax_cross_entropy(onehot_labels=onehot_labels, logits=logits)
# Configure the Training Op (for TRAIN mode)
if mode == tf.estimator.ModeKeys.TRAIN:
optimizer = tf.train.GradientDescentOptimizer(learning_rate=1e-2)
train_op = optimizer.minimize(loss=loss, global_step=tf.train.get_global_step())
return tf.estimator.EstimatorSpec(mode=mode, loss=loss, train_op=train_op)
# Add evaluation metrics (for EVAL mode)
eval_metric_ops = {"accuracy": tf.metrics.accuracy(labels=labels, predictions=predictions["classes"])}
return tf.estimator.EstimatorSpec(mode=mode, loss=loss, eval_metric_ops=eval_metric_ops)
def main(argv):
with open("train_images", "rb") as f:
train_images = np.array(pickle.load(f))
with open("train_labels", "rb") as f:
train_labels = np.array(pickle.load(f), dtype=np.int32)
with open("test_images", "rb") as f:
test_images = np.array(pickle.load(f))
with open("test_labels", "rb") as f:
test_labels = np.array(pickle.load(f), dtype=np.int32)
#print(len(train_images[1]), len(train_labels))
classifier = tf.estimator.Estimator(model_fn=cnn_model_fn, model_dir="tmp/cnn_model3")
tensors_to_log = {"probabilities": "softmax_tensor"}
logging_hook = tf.train.LoggingTensorHook(tensors=tensors_to_log, every_n_iter=50)
train_input_fn = tf.estimator.inputs.numpy_input_fn(x={"x": train_images}, y=train_labels, batch_size=500, num_epochs=10, shuffle=True)
classifier.train(input_fn=train_input_fn, hooks=[logging_hook])
# Evaluate the model and print results
eval_input_fn = tf.estimator.inputs.numpy_input_fn(
x={"x": test_images},
y=test_labels,
num_epochs=1,
shuffle=False)
test_results = classifier.evaluate(input_fn=eval_input_fn)
print(test_results)
if __name__ == "__main__":
tf.app.run()My error is Traceback (most recent call last):
Error:
File "C:\Users\NTU\Desktop\Sign-Language-master\cnn_tf.py", line 1, in <module>
import tensorflow as tf
File "C:\Users\NTU\Anaconda3\envs\dip\lib\site-packages\tensorflow\__init__.py", line 22, in <module>
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "C:\Users\NTU\Anaconda3\envs\dip\lib\site-packages\tensorflow\python\__init__.py", line 27, in <module>
import ctypes
File "C:\Users\NTU\Anaconda3\envs\dip\lib\ctypes\__init__.py", line 7, in <module>
from _ctypes import Union, Structure, Array
ImportError: DLL load failed: %1 is not a valid Win32 application.this:
Anyone can help me
