add docs

.gitattributes

@@ -42,3 +42,4 @@ content/example_1.jpg filter=lfs diff=lfs merge=lfs -text
 content/output_0.png filter=lfs diff=lfs merge=lfs -text
 content/output_1.png filter=lfs diff=lfs merge=lfs -text
 content/Schermafbeelding[[:space:]]2023-05-05[[:space:]]om[[:space:]]14.29.39.png filter=lfs diff=lfs merge=lfs -text
+content/* filter=lfs diff=lfs merge=lfs -text

app.py

@@ -284,7 +284,7 @@ def main():
                     "in almost 30 design styles. After fetching all these images, we started adding metadata such as "
                     "captions (from the BLIP captioning model) and segmentation maps (from the HuggingFace UperNetForSemanticSegmentation model). "
                     )
-            st.write("For the gathering and inference of the metadata we used the Fondant framework (https://github.com/ml6team/fondant) made by ML6 (https://www.ml6.eu/), which is an open source "
+            st.write("For the gathering and inference of the metadata we used the Fondant framework (https://github.com/ml6team/fondant) provided by ML6 (https://www.ml6.eu/), which is an open source "
                      "data centric framework for data preparation. The pipeline used for training this controlnet will soon be available as an "
                      "example pipeline within Fondant and can be easily adapted for building your own dataset."
                      )
@@ -322,6 +322,7 @@ def main():
         
         st.session_state['example_image_0'] = Image.open("content/example_0.png")
         st.session_state['example_image_1'] = Image.open("content/example_1.jpg")
+        st.session_state['example_image_2'] = Image.open("content/example_2.jpg")
         
         col_im_0, col_im_1 = st.columns(2)
         
@@ -329,6 +330,10 @@ def main():
             st.image(st.session_state['example_image_0'], caption="Example image 1", use_column_width=True)
             if st.button("Use example 1"):
                 move_image('example_image_0', 'initial_image', remove_state=True, rerun=True)
+
+            st.image(st.session_state['example_image_2'], caption="Example image 3", use_column_width=True)
+            if st.button("Use example 2"):
+                move_image('example_image_2', 'initial_image', remove_state=True, rerun=True)
         with col_im_1:
             st.image(st.session_state['example_image_1'], caption="Example image 2", use_column_width=True)
             if st.button("Use example 2"):
@@ -367,4 +372,6 @@ def main():
             make_output_image()
 
 if __name__ == "__main__":
-    main()
+    main()
+    
+    

explanation.py

@@ -27,4 +27,25 @@ def make_regeneration_explanation():
         st.image("content/regen_example.png", caption="Room where all concepts except for 'bed', 'lamp', 'table' are regenerated")
 
 def make_segmentation_explanation():
-    pass
+    with st.expander("Segmentation mode", expanded=False):
+        st.write("In the segmentation mode, the user can use his imagination and the paint brush to place concepts in the image. "
+                 "In the left sidebar, you can first find the high level category of the concept you want to add, such as 'lighting', 'floor', .. "
+                 "After selecting the category, you can select the specific concept you want to add in the 'Choose a color' dropdown. "
+                 "This will change the color of the paint brush, which you can then use to draw on the input image. "
+                 "The model will then regenerate the image with the concepts you have drawn and leave the rest of the image unchanged. "
+                 )
+        st.image("content/sidebar segmentation.png", caption="Sidebar with segmentation options", width=300)
+        st.write("You can choose the freedraw mode which gives you a pencil of a certain (chosen) width or the polygon mode. With the polygon mode you can click to add a point to the polygon and close the polygon by right clicking. ")
+        st.write("Important: "
+                 "it's not easy to draw a good segmentation mask. This is because you need to keep in mind the perspective of the room and the exact "
+                 "shape of the object you want to draw within this perspective. Controlnet will follow your segmentation mask pretty well, so "
+                 "a non-natural object shape will sometimes result in weird outputs. However, give it a try and see what you can do! "
+                 )
+        st.image("content/segmentation window.png", caption="Example of a segmentation mask drawn on the input image to add a window to the room")
+        st.write("Tip: ")
+        st.write("In the concepts dropdown, you can select 'keep background' (which is a white color). Everything drawn in this color will use "
+                 "the original underlying segmentation mask. This can be useful to help with generating other objects, since you give the model a some "
+                 "freedom to generate outside the object borders."
+                 )
+        st.image("content/keep background 1.png", caption="Image with a poster drawn on the wall.")
+        st.image("content/keep background 2.png", caption="Image with a poster drawn on the wall surrounded by 'keep background'.")