Upload Home.py with huggingface_hub

Home.py

@@ -0,0 +1,171 @@
+import neural_style
+
+import streamlit as st
+import os 
+import random
+import numpy as np
+from  PIL import Image, ImageEnhance
+from io import BytesIO
+import matplotlib.pyplot as plt
+#import streamlit_ext as ste #for download button not to rerun
+from huggingface_hub import upload_file
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+st.set_page_config(layout="wide")
+
+st.markdown('<p class="font">Afrodreams.AI</p>', unsafe_allow_html=True)
+st.subheader("This app takes in your image and styles it with a unique african art.")
+
+#Create two columns with different width
+col1, col2 = st.columns( [0.8, 0.2])
+import time
+
+
+
+with col1:               # To display the header text using css style
+    st.markdown(""" <style> .font {
+    font-size:35px ; font-family: 'Cooper Black'; color: #FF9633;} 
+    </style> """, unsafe_allow_html=True)
+    st.markdown('<p class="font">Upload your photo here...</p>', unsafe_allow_html=True)
+    
+    
+
+#with st.sidebar.expander("About the App"):
+#     st.write("""
+#       This app takes in your image and styles it with a unique african art.""")
+
+
+#Add file uploader to allow users to upload photos
+uploaded_file = st.file_uploader("", type=['jpg','png','jpeg'])
+
+# add slider to side bar
+style_weight = st.slider("Select Style Weight", min_value=10, max_value=100, value=12)
+img_size_slider= st.select_slider(label= 'Seleet Output Quality Level',
+                                         options = ['Very Low', 'Low', 'Normal', 'High', 'Very High'],
+                                         value='Normal')
+img_size_mapping  = {'Very Low':128, 'Low':300, 'Normal':400, 'High':500, 'Very High':600}
+
+
+def get_random_subset(list_, num_imgs):
+    return random.sample(list_, num_imgs)
+
+
+def display_random_images(five_rand_imgs, display_type, size= (15, 6)):
+    fig = plt.figure(figsize=size)
+    fig.subplots_adjust(wspace=0.2) 
+    for i in range(1, len(five_rand_imgs)+1):
+        ith_image = Image.open(five_rand_imgs[i-1])
+    
+        ax = fig.add_subplot(1, 5, i)
+        ax.imshow(ith_image)
+        ax.set_title(f'{display_type} {i}')
+        plt.axis('off')
+    
+    st.pyplot(fig)
+
+def select_title_from_check_box(index, names_dict):
+    return names_dict[index]
+def format_func(five_rand_imgs):
+    st.write(' the lenght is', len(five_rand_imgs))
+    return list(range(len(five_rand_imgs)))
+path = 'stylesv2'
+    
+    
+#expander for style selection
+with st.expander("Expand to select style type"):
+    img_names = [os.path.join(path, img) for img in os.listdir(path)]
+    five_rand_imgs0 = get_random_subset(img_names, 5)
+    if 'selected_image' not in st.session_state:
+        st.session_state.selected_image = five_rand_imgs0
+    five_rand_imgs = st.session_state.selected_image   
+    display_random_images(five_rand_imgs, 'Style')
+    chosen_style = st.selectbox(
+    'Select the style you want to use',
+    options = five_rand_imgs, format_func = lambda x: "Style " + str(five_rand_imgs.index(x) + 1),
+    key= 'expander1'
+    )
+    
+ 
+
+#put notificaation
+with st.empty():
+    for seconds in range(5):
+        st.info('Please note that by using this app, you agree that your image  be will be showcased on this app.')
+        time.sleep(1)
+    st.empty()
+
+#Add 'before' and 'after' columns
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    
+    col1, col2 = st.columns( [0.5, 0.5])
+    with col1:
+        st.markdown('<p style="text-align: center;">Before</p>',unsafe_allow_html=True)
+        st.image(image,width=300)  
+
+    with col2:
+        st.markdown('<p style="text-align: center;">After</p>',unsafe_allow_html=True)
+        
+    # add a button
+    run = st.button('Generate Art')
+    my_bar = st.progress(0)
+    params = neural_style.TransferParams()
+    params.gpu = "c"
+    params.backend = "mkl"
+
+    
+    params.image_size = img_size_mapping[img_size_slider]
+    
+    params.content_image = uploaded_file
+    params.style_weight = style_weight
+
+
+
+    keep_style = False
+    if run==True:
+        # run image selection if keep style is false
+        if keep_style==False:
+            
+            styles = os.listdir(path)
+            #params.style_image = path + '/' + random.choice(styles)
+            params.style_image = chosen_style
+            
+        st.session_state.submitted = True   
+        with st.spinner('Wait for it...'): 
+            neural_style.transfer(params)
+
+        #display image when done.
+        with col2:
+            if 'submitted' in st.session_state:
+                result = Image.open('out.png')
+                st.image(result, width=300)
+                buf = BytesIO()
+                result.save(buf, format="png")
+                if len(os.listdir('generated_samples')) <= 10:
+                    img_file_name = f"generated_samples/{str(len(os.listdir('generated_samples')))}.png"
+                
+                    _ = upload_file(path_or_fileobj = 'out.png',
+                            path_in_repo = img_file_name,
+                            repo_id='AfrodreamsAI/afrodreams',
+                            repo_type='space',
+                            token=HF_TOKEN
+                        ) 
+                    
+                byte_im = buf.getvalue()
+                #run =ste.download_button(button_text="Download Image", data=byte_im, download_filename='afrodreams.jpg', mime="image/png")
+                
+
+
+
+# selectiuing random iamges to be displayed
+img_names = [os.path.join('generated_samples', img) for img in os.listdir('generated_samples')]
+five_rand_imgs1 = get_random_subset(img_names, 5)
+st.subheader('\n\n\n\n\n\n\n\n Examples of some Generate Images')
+display_random_images(five_rand_imgs1, 'Generate image', size=(20, 15))
+
+        
+
+
+
+