support free image ratios

app.py

@@ -37,12 +37,25 @@ def main():
         if input_image is None:
             raise gr.Error("No image uploaded!")
 
-    def preprocess(image):
-        image = TTF.resize(
-            image, (cfg.dataset.height, cfg.dataset.width), 
-            interpolation=TT.InterpolationMode.BICUBIC
-        )
-        image = pad_border_fn(image)
+    def preprocess(image, dynamic_size=False, padding=True):
+        w, h = image.size
+        size = 32
+        if dynamic_size:
+            while max(h, w) // size > 20:
+                size *=2
+            image = TTF.center_crop(image, (h // size * size, w // size * size))
+            image = TTF.resize(image, (h // size * 32, w // size * 32), interpolation=TT.InterpolationMode.BICUBIC)
+            model.cfg.dataset.width, model.cfg.dataset.height = image.size
+            model.set_backproject()
+        else:
+            image = TTF.resize(
+                image, (cfg.dataset.height, cfg.dataset.width), 
+                interpolation=TT.InterpolationMode.BICUBIC
+            )
+        if padding:
+            image = pad_border_fn(image)
+        else:
+            model.cfg.dataset.pad_border_aug = 0
         return image
 
     @spaces.GPU()
@@ -58,7 +71,12 @@ def main():
         outputs = model(inputs)
 
         # export reconstruction to ply
-        save_ply(outputs, ply_out_path, num_gauss=2)
+        save_ply(outputs, 
+                 ply_out_path,
+                 num_gauss=model.cfg.model.gaussians_per_pixel,
+                 h=model.cfg.dataset.height,
+                 w=model.cfg.dataset.width,
+                 pad=model.cfg.dataset.pad_border_aug)
 
         return ply_out_path
     
@@ -93,6 +111,10 @@ def main():
                     )
                 with gr.Row():
                     submit = gr.Button("Generate", elem_id="generate", variant="primary")
+                
+                with gr.Row():
+                        dynamic_size = gr.Checkbox(True, interactive=True, label='Use the original image ration')
+                        padding = gr.Checkbox(True, interactive=True, label='add padding to the image')
 
                 with gr.Row(variant="panel"): 
                     gr.Examples(
@@ -102,6 +124,11 @@ def main():
                             './demo_examples/kitti_03.png',
                             './demo_examples/re10k_05.jpg',
                             './demo_examples/re10k_06.jpg',
+                            './demo_examples/christ_church_cathedral.png',
+                            './demo_examples/radcliffe.png',
+                            './demo_examples/blenheim_palace_bedroom.png',
+                            './demo_examples/blenheim_palace_living.png',
+                            './demo_examples/blenheim_palace.JPG',
                         ],
                         inputs=[input_image],
                         cache_examples=False,
@@ -116,7 +143,7 @@ def main():
                 with gr.Row():
                     with gr.Tab("Reconstruction"):
                         output_model = gr.Model3D(
-                            height=512,
+                            height=640,
                             label="Output Model",
                             interactive=False
                         )
@@ -124,7 +151,7 @@ def main():
         gr.Markdown(
         """
             ## Comments:
-            1. If you run the demo online, the first example you upload should take about 25 seconds (with preprocessing, saving and overhead), the following take about 14s.
+            1. If you run the demo online, the first example you upload should take about 25 seconds (with preprocessing, saving and overhead), the following take about 14s (due to the .ply visualisation).
             2. The 3D viewer shows a .ply mesh extracted from a mix of 3D Gaussians. This is only an approximations and artefacts might show.
             3. Known limitations include:
             - a black dot appearing on the model from some viewpoints
@@ -145,7 +172,7 @@ def main():
 
         submit.click(fn=check_input_image, inputs=[input_image]).success(
             fn=preprocess,
-            inputs=[input_image],
+            inputs=[input_image, dynamic_size, padding],
             outputs=[processed_image],
         ).success(
             fn=reconstruct_and_export,