Spaces:
Running
Running
add SRGAN
Browse files- .gitignore +2 -1
- app.py +29 -1
- models/SRGAN/srgan.py +73 -0
- models/SRGAN/srgan_checkpoint.pth +3 -0
.gitignore
CHANGED
@@ -1,4 +1,5 @@
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models/HAT/__pycache__/hat.cpython-39.pyc
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/.venv
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/models/HAT/__pycache__
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-
/models/RCAN/__pycache__
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models/HAT/__pycache__/hat.cpython-39.pyc
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/.venv
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/models/HAT/__pycache__
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/models/RCAN/__pycache__
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/models/SRGAN/__pycache__
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app.py
CHANGED
@@ -5,6 +5,7 @@ from PIL import Image
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from io import BytesIO
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from models.HAT.hat import *
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from models.RCAN.rcan import *
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# Initialize session state for enhanced images
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if 'hat_enhanced_image' not in st.session_state:
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@@ -13,11 +14,17 @@ if 'hat_enhanced_image' not in st.session_state:
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if 'rcan_enhanced_image' not in st.session_state:
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st.session_state['rcan_enhanced_image'] = None
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if 'hat_clicked' not in st.session_state:
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st.session_state['hat_clicked'] = False
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if 'rcan_clicked' not in st.session_state:
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st.session_state['rcan_clicked'] = False
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-
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st.markdown("<h1 style='text-align: center'>Image Super Resolution</h1>", unsafe_allow_html=True)
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# Sidebar for navigation
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st.sidebar.title("Options")
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@@ -38,8 +45,10 @@ elif app_mode == "Take a photo":
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def reset_states():
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st.session_state['hat_enhanced_image'] = None
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st.session_state['rcan_enhanced_image'] = None
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st.session_state['hat_clicked'] = False
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st.session_state['rcan_clicked'] = False
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def get_image_download_link(img, filename):
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"""Generates a link allowing the PIL image to be downloaded"""
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@@ -93,3 +102,22 @@ if 'image' in locals():
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col2.image(st.session_state['rcan_enhanced_image'], use_column_width=True)
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with col2:
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get_image_download_link(st.session_state['rcan_enhanced_image'], 'rcan_enhanced.jpg')
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from io import BytesIO
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from models.HAT.hat import *
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from models.RCAN.rcan import *
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from models.SRGAN.srgan import *
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# Initialize session state for enhanced images
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if 'hat_enhanced_image' not in st.session_state:
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if 'rcan_enhanced_image' not in st.session_state:
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st.session_state['rcan_enhanced_image'] = None
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if 'srgan_enhanced_image' not in st.session_state:
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st.session_state['srgan_enhanced_image'] = None
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if 'hat_clicked' not in st.session_state:
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st.session_state['hat_clicked'] = False
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if 'rcan_clicked' not in st.session_state:
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st.session_state['rcan_clicked'] = False
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if 'srgan_clicked' not in st.session_state:
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st.session_state['srgan_clicked'] = False
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st.markdown("<h1 style='text-align: center'>Image Super Resolution</h1>", unsafe_allow_html=True)
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# Sidebar for navigation
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st.sidebar.title("Options")
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def reset_states():
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st.session_state['hat_enhanced_image'] = None
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st.session_state['rcan_enhanced_image'] = None
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st.session_state['srgan_enhanced_image'] = None
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st.session_state['hat_clicked'] = False
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st.session_state['rcan_clicked'] = False
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st.session_state['srgan_clicked'] = False
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def get_image_download_link(img, filename):
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"""Generates a link allowing the PIL image to be downloaded"""
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col2.image(st.session_state['rcan_enhanced_image'], use_column_width=True)
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with col2:
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get_image_download_link(st.session_state['rcan_enhanced_image'], 'rcan_enhanced.jpg')
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#--------------------------SRGAN--------------------------#
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if st.button('Enhance with SRGAN'):
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with st.spinner('Processing using SRGAN...'):
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with st.spinner('Wait for it... the model is processing the image'):
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srgan_model = GeneratorResnet()
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device = torch.device('cpu') if not torch.cuda.is_available() else torch.device('cuda')
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srgan_model = torch.load('models/SRGAN/srgan_checkpoint.pth', map_location=device)
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enhanced_image = srgan_model.inference(image)
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st.session_state['srgan_enhanced_image'] = enhanced_image
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st.session_state['srgan_clicked'] = True
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st.success('Done!')
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if st.session_state['srgan_enhanced_image'] is not None:
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col1, col2 = st.columns(2)
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col1.header("Original")
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col1.image(image, use_column_width=True)
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col2.header("Enhanced")
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col2.image(st.session_state['srgan_enhanced_image'], use_column_width=True)
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with col2:
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get_image_download_link(st.session_state['srgan_enhanced_image'], 'srgan_enhanced.jpg')
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models/SRGAN/srgan.py
ADDED
@@ -0,0 +1,73 @@
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import os
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import torch
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from torch import nn
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from PIL import Image
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from torchvision.transforms import ToTensor
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class ResidualBlock(nn.Module):
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def __init__(self, in_features):
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super(ResidualBlock, self).__init__()
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self.conv_block = nn.Sequential(
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nn.Conv2d(in_features, in_features, kernel_size=3, stride=1, padding=1),
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nn.BatchNorm2d(in_features, 0.8),
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nn.PReLU(),
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nn.Conv2d(in_features, in_features, kernel_size=3, stride=1, padding=1),
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nn.BatchNorm2d(in_features, 0.8),
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)
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def forward(self, x):
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return x + self.conv_block(x)
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class GeneratorResnet(nn.Module):
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def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16):
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super(GeneratorResnet, self).__init__()
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#first layer
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self.conv1 = nn.Sequential(nn.Conv2d(in_channels, 64, kernel_size=9, stride=1, padding=4), nn.PReLU())
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#Residual blocks
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res_blocks=[]
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for _ in range(n_residual_blocks):
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res_blocks.append(ResidualBlock(64))
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self.res_blocks = nn.Sequential(*res_blocks)
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#second conv layer after res blocks
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self.conv2 = nn.Sequential(nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1), nn.BatchNorm2d(64, 0.8))
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upsampling=[]
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for _ in range(2):
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upsampling+=[
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nn.Conv2d(64, 256, kernel_size=3, stride=1, padding=1),
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nn.BatchNorm2d(256),
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nn.PixelShuffle(upscale_factor=2),
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nn.PReLU(),
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]
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self.upsampling = nn.Sequential(*upsampling)
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self.conv3 = nn.Sequential(nn.Conv2d(64, out_channels, kernel_size=9, stride=1, padding=4), nn.Tanh())
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def forward(self, x):
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out1 = self.conv1(x)
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out = self.res_blocks(out1)
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out2 = self.conv2(out)
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out = torch.add(out1, out2)
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out = self.upsampling(out)
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out = self.conv3(out)
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return out
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def inference(self, x):
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"""
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x is a PIL image
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"""
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x = ToTensor()(x).unsqueeze(0)
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x = self.forward(x)
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x = Image.fromarray((x.squeeze(0).permute(1, 2, 0).detach().numpy() * 255).astype('uint8'))
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return x
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if __name__ == '__main__':
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current_dir = os.path.dirname(os.path.realpath(__file__))
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model = GeneratorResnet()
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model = torch.load(current_dir + '/srgan_checkpoint.pth', map_location=torch.device('cpu'))
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model.eval()
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with torch.no_grad():
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input_image = Image.open('images/demo.png')
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output_image = model.inference(input_image)
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models/SRGAN/srgan_checkpoint.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b1423b711b26b2250612e02fddf95a4a7214e883c601eb153bfa82caceb5511
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size 6336189
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