def main():
#If there's no argument, run basic demonstration
if (len(sys.argv) == 1):
style_transfer("./images/all/man_with_sunglasses.jpg",
"./images/all/stained_glass_1.jpg",
"./output/stained_glasses_man.jpg",
max_size=150 * 150)
#If there's three arguments, run a basic iteration with only path names.
elif (len(sys.argv) == 4):
style_transfer(sys.argv[1],
sys.argv[2],
sys.argv[3],
max_size=150 * 150)
else:
print(
"Please enter no arguments for a basic demonstration, or three arguments with the content, style and output images file path."
)
print(
"For more parameters please open this script and run it from an interpreter."
)
def webcam_input(model):
st.header("Webcam Live Feed")
run = st.checkbox("Run")
FRAME_WINDOW = st.image([], channels='BGR')
SIDE_WINDOW = st.sidebar.image([], width=100, channels='BGR')
camera = cv2.VideoCapture(0)
WIDTH = st.sidebar.select_slider('QUALITY (May reduce the speed)', list(range(150, 501, 50)))
while run:
_, frame = camera.read()
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
# orig = frame.copy()
orig = imutils.resize(frame, width=300)
frame = imutils.resize(frame, width=WIDTH)
target = style_transfer(frame, model)
FRAME_WINDOW.image(target)
SIDE_WINDOW.image(orig)
else:
st.warning("NOTE: Streamlit currently doesn't support webcam. So to use this, clone this repo and run it on local server.")
st.warning('Stopped')
def image_input(model):
if st.sidebar.checkbox('Upload'):
content_file = st.sidebar.file_uploader("Choose a Content Image", type=["png", "jpg", "jpeg"])
else:
content_name = st.sidebar.selectbox("Choose the content images:", content_images_name)
content_file = content_images_dict[content_name]
if content_file is not None:
content = Image.open(content_file)
content = np.array(content) #pil to cv
content = cv2.cvtColor(content, cv2.COLOR_RGB2BGR)
else:
st.warning("Upload an Image OR Untick the Upload Button)")
st.stop()
WIDTH = st.sidebar.select_slider('QUALITY (May reduce the speed)', list(range(150, 501, 50)), value=200)
content = imutils.resize(content, width=WIDTH)
generated = style_transfer(content, model)
st.sidebar.image(content, width=300, channels='BGR')
st.image(generated, channels='BGR', clamp=True)
content_images_name)
content_file = content_images_dict[content_name]
if content_file is not None:
content = Image.open(content_file)
content = np.array(content) # pil to cv
content = cv2.cvtColor(content, cv2.COLOR_RGB2BGR)
else:
st.warning("Upload an Image OR Untick the Upload Button)")
st.stop()
# ## Exercise 3 : Render your final results ## #
# 3.1. Create a slider on your sidebar to select the quality
# from 150 to 500, step of 50, default value of 200
# Store this value in a WIDTH variable
WIDTH = st.sidebar.select_slider('QUALITY (May reduce the speed)',
list(range(150, 501, 50)), value=200)
content = imutils.resize(content, width=WIDTH)
generated = style_transfer(content, model)
# 3.2. Show the source image (content) in the sidebar in BGR channel
st.sidebar.image(content, width=300, channels='BGR')
# 3.3 Show the final result (generated) right in your app
st.image(generated, channels='BGR', clamp=True)
#default values : content = 0.025, style = 5.0, var_w = 1.0
content_weight = 0.025
style_weight = 5.0
var_weight = 1.
### Layer used for the Loss calculations
ln_content = ["block5_conv2"]
ln_style = [
"block1_conv1", "block2_conv1", "block3_conv1", "block4_conv1",
"block5_conv1"
]
style_transfer(
content_image_path, #Path of the content image
style_image_path, #Path of the style image
output_image_path, #Path of the output image
loadDims, #True if using native image dim
withBaseImage, #True if using content image as starting image, false for random noises.
rescale, #Rescale the image, only useful if loadDims = true
max_size, #Automatically rescale if height*width > max_size. -1 to ignore.
height, #wanted height of the images, useless if loadDims.
width, #wanted width of the images, useless if loadDims.
nb_iterations, #number of iterations
stepsBeforeSaveAndShow, #
content_weight,
style_weight,
var_weight,
ln_content, #Layers used for loss content calculation
ln_style #Layers used for style content calculation.
)