it looks good with Insta logo

README.md

@@ -4,6 +4,12 @@ TLDR: From generated Image -> Copaint PDF
 [![demo](data/demo.jpg)](data/demo.jpg)
 
 
+```
+git clone https://github.com/ThibaultGROUEIX/copaint.git
+git lfs pull #(install git LFS)
+```
+
+
 ## Usage and Install
 ```
 # Install dependencies
@@ -19,20 +25,20 @@ poetry run copaint-app
 pip install torch torchvision reportlab PyPDF2 Pillow argparse gradio_pdf
 
 # Run
-python copaint.py --input_image data/bear.jpg --copaint_logo data/logo_copaint.jpg --outputfolder output
+python copaint.py --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output
 
 # Using the CLI
 pip install --upgrade pip
 pip install -e .
 
 # Case 1 : generate all the presets
-copaint --input_image data/bear.jpg --copaint_logo data/logo_copaint.jpg --outputfolder output --use_presets True
+copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --use_presets True
 
 # Case 2 : provide a number of participants, the program will generate the best grid
-copaint --input_image data/bear.jpg --copaint_logo data/logo_copaint.jpg --outputfolder output --nparticipants 45 
+copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --nparticipants 45 
 
 # Case 3 : provide the number of cells in the grid
-copaint --input_image data/bear.jpg --copaint_logo data/logo_copaint.jpg --outputfolder output --h_cells 3 --w_cells 4
+copaint --input_image data/bear.jpg --copaint_logo copaint/static/logo_copaint.png --outputfolder output --h_cells 3 --w_cells 4
 ```
 
 ## Build and deploy
@@ -41,4 +47,14 @@ copaint --input_image data/bear.jpg --copaint_logo data/logo_copaint.jpg --outpu
 poetry build
 # Deploy
 poetry publish
-```
+```
+
+## Todo
+-- Preload copaint logo ()
+```
+Loaded image of shape torch.Size([1, 4, 1848, 1844]), from copaint/static/logo_copaint.png
+Image to tensor conversion took 0.0459 seconds
+```
+-- Same for insta logo
+
+

copaint/copaint.py

@@ -86,6 +86,12 @@ def load_image(image_path, debug=False):
         # image.show()
     else:
         image = Image.open(image_path)
+        # convert to RGBA
+        image = image.convert("RGBA")
+        # Apply a white background
+        background = Image.new("RGB", image.size, (255, 255, 255))
+        background.paste(image, mask=image.split()[3])
+        image = background
     
     image_open_time = time.time()
     if debug:
@@ -271,7 +277,7 @@ def create_image_with_text(text: str = "1", size: int = 400, underline: bool = T
     return tensor
 
 
-def create_back_image(h, w, h_cells, w_cells, logo_image, unique_identifier, list_of_cell_idx=None, debug=False):
+def create_back_image(h, w, h_cells, w_cells, logo_image, logo_insta_image, unique_identifier, list_of_cell_idx=None, debug=False):
     """
     Create back image tensor, of size hxw - 
     Black pixels at the separation of cells to draw the lines
@@ -323,12 +329,18 @@ def create_back_image(h, w, h_cells, w_cells, logo_image, unique_identifier, lis
     new_h, new_w = int(h * scale_logo), int(w * scale_logo)
     logo_image_resized = torch.nn.functional.interpolate(logo_image, size=(new_h, new_w), mode='bilinear')
     
+    t_insta = time.time()
+    _, _, h_insta, w_insta = logo_insta_image.size()
+    scale_insta = min(logo_size / h_insta, logo_size / w_insta) / 5
+    new_h_insta, new_w_insta = int(h_insta * scale_insta), int(w_insta * scale_insta)
+    logo_insta_image_resized = torch.nn.functional.interpolate(logo_insta_image, size=(new_h_insta, new_w_insta), mode='bilinear')
     if debug:
-        print(f"Logo resizing took {time.time() - logo_resize_time:.4f} seconds")
-    
+        print(f"Logo resizing took {time.time() - logo_resize_time:.4f} seconds ({time.time() - t_insta:.4f} for insta and {t_insta - logo_resize_time:.4f} for copaint logo)")
+        # save logo_insta_image_resized
+        save_image(logo_insta_image_resized, "logo_insta_image_resized.png", debug=debug)
     # Add content to cells
     cell_content_time = time.time()
-    letscopaint = create_image_with_text("@letscopaint", underline=False, 
+    letscopaint = create_image_with_text("copaint_art", underline=False, 
                                                     size=(int(0.8*number_size), number_size//8), 
                                                     debug=debug)
     for i in range(h_cells):
@@ -368,7 +380,13 @@ def create_back_image(h, w, h_cells, w_cells, logo_image, unique_identifier, lis
             start_letscopaint_h = h1-logo_offset # Fix
             start_letscopaint_w = w0 + unique_identifier_size_h // 16 # Fix
             back_image[:, :, start_letscopaint_h-(number_size//8):start_letscopaint_h, start_letscopaint_w:start_letscopaint_w+(int(0.8*number_size))] = letscopaint[:, :num_channels, :, :]
-    
+
+            # add instagram logo at the bottom left of the cell
+            _, _, h_insta, w_insta  = logo_insta_image_resized.shape
+            start_insta_h = h1-logo_offset # Fix
+            start_insta_w = w0 + unique_identifier_size_h // 6 # Fix
+            back_image[:, :, start_insta_h-(number_size//8):start_insta_h-(number_size//8)+h_insta, start_insta_w:start_insta_w+w_insta] = logo_insta_image_resized[:, :num_channels, :, :]
+            
     if debug:
         print(f"Adding content to cells took {time.time() - cell_content_time:.4f} seconds")
         print(f"Created back image of shape {back_image.shape}")
@@ -389,12 +407,22 @@ def image_to_pdf_core(input_image, file_name, logo_image, outputfolder, h_cells,
         image = load_image(input_image, debug=debug)
     else:
         image = input_image
-  
+    if debug:
+        print(f"Image loading took {time.time() - t1:.4f} seconds")
+    
     _, c, h, w = image.shape
     print(f"Image shape: {image.shape}")
+
+    t1_2 = time.time()
     logo_image = load_image(logo_image, debug=debug)
+
     if debug:
-        print(f"Image loading took {time.time() - t1:.4f} seconds")
+        print(f"Logo copaint Image loading took {time.time() - t1_2:.4f} seconds")
+    
+    t1_3 = time.time()
+    logo_insta_image = load_image("./copaint/static/logo_instagram.png", debug=debug)
+    if debug:
+        print(f"Logo instagram Image loading took {time.time() - t1_3:.4f} seconds")
     
     # # Quick check that the greatest dimension corresponds to the greatest number of cells
     # if h > w and h_cells < w_cells:
@@ -412,7 +440,7 @@ def image_to_pdf_core(input_image, file_name, logo_image, outputfolder, h_cells,
         scale_3 = max(multiplier_w, multiplier_h)
 
     print(f"Creating back image with {h*scale_3} x {w*scale_3} pixels for {h_cells} x {w_cells} cells")
-    back_image = create_back_image(h*scale_3, w*scale_3, h_cells, w_cells, logo_image, 
+    back_image = create_back_image(h*scale_3, w*scale_3, h_cells, w_cells, logo_image, logo_insta_image,
                                   unique_identifier=unique_identifier, list_of_cell_idx=list_of_cell_idx,  debug=debug)
     if debug:
         save_image(back_image, os.path.join(outputfolder, "back_image.png"), debug=debug)

copaint/gradio_ui.py

@@ -201,7 +201,7 @@ def build_gradio_ui():
 
                                 cell_size = gr.Number(label="Square Size, in cm (optional)",
                                                       value="",
-                                                      info="If none is provided, the design size automatically adjusts to fit on a single page.")
+                                                      info="If none is provided, the design size automatically adjusts to fit on a single page. In most situations, you don't need this.")
 
                                 copaint_name = gr.Textbox(label="Add a Custom Design Name (optional)",
                                                           value="",