dogeplusplus commited on
Commit
eb8f9d9
·
1 Parent(s): 80446b6

Widgets to display FPS, flags to disable camera.

Browse files
template_styles/cogs.jpg DELETED
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webcam_stream.py CHANGED
@@ -1,6 +1,9 @@
 
1
  import cv2
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- import tensorflow as tf
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  import numpy as np
 
 
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  from threading import Thread
5
 
6
 
@@ -29,30 +32,81 @@ class WebcamVideoStream:
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30
 
31
  def style_transfer_direct(image, style_image, model, resize=None):
 
32
  if resize:
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  image = cv2.resize(np.array(image, dtype=np.float32), (512, 512))
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  else:
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  image = np.array(image, dtype=np.float32)
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- resp = model(tf.convert_to_tensor(image[np.newaxis, ...] / 255.), tf.convert_to_tensor(style_image))
 
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  stylized_image = resp[0]
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  return stylized_image.numpy()[0]
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  def main():
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  model = tf.saved_model.load('style/1')
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- video_capture = WebcamVideoStream('http://192.168.0.10:4747/video')
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- video_capture.start()
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-
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- style_image = np.array(cv2.imread('/home/albert/Downloads/pattern.jpeg'), dtype=np.float32)[np.newaxis, ...] / 255.
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-
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- while True:
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- content_image = video_capture.read()
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- transfer = style_transfer_direct(content_image, style_image, model)
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- cv2.imshow('style camera', transfer)
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- if cv2.waitKey(1) & 0xFF == ord('q'):
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- break
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- cv2.destroyAllWindows()
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- video_capture.stop()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  if __name__ == "__main__":
 
1
+ import os
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  import cv2
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+ import time
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  import numpy as np
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+ import streamlit as st
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+ import tensorflow as tf
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  from threading import Thread
8
 
9
 
 
32
 
33
 
34
  def style_transfer_direct(image, style_image, model, resize=None):
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+ image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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  if resize:
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  image = cv2.resize(np.array(image, dtype=np.float32), (512, 512))
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  else:
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  image = np.array(image, dtype=np.float32)
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+ image = tf.convert_to_tensor(image[np.newaxis, ...] / 255.)
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+ resp = model(image, style_image)
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  stylized_image = resp[0]
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  return stylized_image.numpy()[0]
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+ def get_style_dictionary():
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+ style_lookup = {}
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+ for file in os.listdir('assets/template_styles'):
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+ with open(os.path.join('assets/template_styles', file), 'rb') as f:
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+ style = f.read()
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+ style_image = tf.io.decode_image(style)
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+ style_image = np.array(style_image[np.newaxis, ...], dtype=np.float32) / 255.
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+ style_image = tf.image.resize(style_image, (256, 256))
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+ style_image = tf.convert_to_tensor(style_image)
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+ style_lookup[file] = style_image
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+ return style_lookup
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+
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+ @st.cache(persist=True)
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+ def get_custom_style(image_bytes):
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+ style_image = tf.io.decode_image(image_bytes)
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+ style_image = np.array(style_image[np.newaxis, ...], dtype=np.float32) / 255.
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+ style_image = tf.image.resize(style_image, (256, 256))
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+ style_image = tf.convert_to_tensor(style_image)
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+ return style_image
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+
66
+
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  def main():
68
  model = tf.saved_model.load('style/1')
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+ st.title("Neural Style-Transfer Webcam")
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+ st.subheader('Style Transfer')
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+ webcam_flag = st.sidebar.checkbox('Enable Webcam', value=False)
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+ style_flag = st.sidebar.checkbox('Enable Style Transfer', value=False)
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+ with open('assets/bonk.png', 'rb') as f:
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+ default_bytes = f.read()
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+ placeholder_image = st.image(default_bytes)
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+
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+ style_dictionary = get_style_dictionary()
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+ style_options = st.sidebar.selectbox(label='Example Styles', options=list(style_dictionary.keys()))
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+ custom_style = st.sidebar.file_uploader('Upload Style:', type=['.jpg', '.jpeg', '.png'])
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+ frame_rate = st.text(f'Frames per second: 0')
81
+
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+ if webcam_flag:
83
+ video_capture = WebcamVideoStream('http://192.168.0.10:4747/video')
84
+ start = time.time()
85
+ total_frames = 0
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+ try:
87
+ video_capture.start()
88
+ if custom_style is not None:
89
+ custom_style_bytes = custom_style.getvalue()
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+ style_image = get_custom_style(custom_style_bytes)
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+ else:
92
+ style_image = style_dictionary[style_options]
93
+
94
+ st.sidebar.subheader("Style Image:")
95
+ st.sidebar.image(np.array(style_image.numpy()[0] * 255., dtype=np.uint8), use_column_width=True)
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+
97
+ while webcam_flag:
98
+ content_image = video_capture.read()
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+ if style_flag:
100
+ transfer = style_transfer_direct(content_image, style_image, model)
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+ placeholder_image.image(transfer)
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+ else:
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+ placeholder_image.image(content_image, channels='BGR')
104
+ total_frames += 1
105
+ end = time.time()
106
+ frame_rate.text(f'Frames per second: {total_frames / (end - start)}')
107
+ finally:
108
+ video_capture.stop()
109
+ del video_capture
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111
 
112
  if __name__ == "__main__":