added examples

app.py

@@ -13,8 +13,8 @@ import sys
 sys.path.append('/home/user/app/code')
 
 # set up diffvg
-
 # os.system('git clone https://github.com/BachiLi/diffvg.git')
+
 os.system('git submodule update --init')
 os.chdir('diffvg')
 os.system('git submodule update --init --recursive')
@@ -50,16 +50,20 @@ from utils import (
     combine_word)
 import warnings
 
-TITLE="""<h1 style="font-size: 42px;" align="center">Text-To-Image: Morphing Arabic Text to Image</h1>"""
-DESCRIPTION="""A demo for [Word-As-Image for Semantic Typography](https://wordasimage.github.io/Word-As-Image-Page/). By using Word-as-Image, a visual representation of the meaning of the word is created while maintaining legibility of the text and font style. 
-Please select a semantic concept word and a letter you wish to generate, it will take ~5 minutes to perform 500 iterations."""
+TITLE="""<h1 style="font-size: 42px;" align="center">Word-To-Image: Morphing Arabic Text to a Visual Representation</h1>"""
+
 
-DESCRIPTION="""This demo builds on the [Word-As-Image for Semantic Typography](https://wordasimage.github.io/Word-As-Image-Page/) work to support Arabic fonts and morphing whole words into semantic concepts."""
+DESCRIPTION="""This demo builds on the [Word-As-Image for Semantic Typography](https://wordasimage.github.io/Word-As-Image-Page/) work to support Arabic fonts and morphing whole words into semantic concepts. It is part of an ongoing project with the [ARBML](https://arbml.github.io/website/) community."""
 
 # DESCRIPTION += '\n<p>This demo is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"> Creative Commons Attribution-ShareAlike 4.0 International License</a>.</p>'
+# DESCRIPTION += """<br>For faster inference without waiting in queue, you can [![]()]()"""
+DESCRIPTION += '\n<p>For faster inference without waiting in queue, you can <a href="https://colab.research.google.com/drive/1wobOAsnLpkIzaRxG5yac8NcV7iCrlycP"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a></p>'
 
 if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
-    DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
+    DESCRIPTION = DESCRIPTION.replace("</p>", " ")
+    DESCRIPTION += f'or duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
+else:
+    DESCRIPTION = DESCRIPTION.replace("either", "")
 
 
 warnings.filterwarnings("ignore")
@@ -145,7 +149,9 @@ def init_shapes(svg_path, trainable: Mapping[str, bool]):
     return shapes_init, shape_groups_init, parameters
 
 
-def run_main_ex(semantic_concept, word, prompt, font_name, num_steps):
+def run_main_ex(word, semantic_concept, num_steps):
+    prompt = f"a {semantic_concept}. minimal flat 2d vector. lineal color. trending on artstation"
+    font_name = "ArefRuqaa"
     return list(next(run_main_app(semantic_concept, word, prompt, font_name, num_steps, 1)))
                         
 def run_main_app(semantic_concept, word, prompt, font_name, num_steps, example=0):
@@ -240,7 +246,7 @@ def run_main_app(semantic_concept, word, prompt, font_name, num_steps, example=0
     save_svg.save_svg(
         filename, w, h, shapes, shape_groups)
 
-    combine_word(cfg.word, cfg.optimized_letter, cfg.font, cfg.experiment_dir)
+    combine_word(cfg.word, cfg.optimized_letter, cfg.font, cfg.experiment_dir, device)
 
     image = os.path.join(cfg.experiment_dir,f"{cfg.font}_{cfg.word}_{cfg.optimized_letter}.svg")
     yield gr.update(value=filename_init,visible=True),gr.update(visible=False),gr.update(value=image,visible=True)
@@ -314,51 +320,25 @@ with gr.Blocks() as demo:
     with gr.Row():
         # examples
         examples = [
-            [
-            "BUNNY",
-            "BUNNY",
-            "Y",
-            "KaushanScript-Regular",
-            500
-            ],
-            [
-            "LION",
-            "LION",
-            "O",
-            "Quicksand",
-            500
-            ],
-            [
-            "FROG",
-            "FROG",
-            "G",
-            "IndieFlower-Regular",
-            500
-            ],
-            [
-            "CAT",
-            "CAT",
-            "C",
-            "LuckiestGuy-Regular",
-            500
-            ],
+            ["قطة", "Cat", 500],
+            ["كلب", "Dog", 500],
+            ["حصان", "Horse", 500],
+            ["أخطبوط", "Octopus", 500],
         ]
         demo.queue(max_size=10, concurrency_count=2)
-        # gr.Examples(examples=examples,
-        #         inputs=[
-        #             semantic_concept,
-        #             word,
-        #             letter, 
-        #             font_name,
-        #             num_steps
-        #         ],
-        #         outputs=[
-        #             result0,
-        #             result1,
-        #             result2
-        #         ],
-        #         fn=run_main_ex,
-        #         cache_examples=True)
+        gr.Examples(examples=examples,
+                inputs=[
+                    word,
+                    semantic_concept,
+                    num_steps
+                ],
+                outputs=[
+                    result0,
+                    result1,
+                    result2
+                ],
+                fn=run_main_ex,
+                cache_examples=False)
         
         
     # inputs

code/utils.py

@@ -142,7 +142,7 @@ def get_letter_ids(letter, word, shape_groups):
             return group.shape_ids
 
 
-def combine_word(word, letter, font, experiment_dir):
+def combine_word(word, letter, font, experiment_dir, device='cuda'):
     word_svg_scaled = f"./code/data/init/{font}_{word}_scaled.svg"
     canvas_width_word, canvas_height_word, shapes_word, shape_groups_word = pydiffvg.svg_to_scene(word_svg_scaled)
 
@@ -202,7 +202,7 @@ def combine_word(word, letter, font, experiment_dir):
     scene_args = pydiffvg.RenderFunction.serialize_scene(canvas_width, canvas_height, shapes_word, shape_groups_word)
     img = render(canvas_width, canvas_height, 2, 2, 0, None, *scene_args)
     img = img[:, :, 3:4] * img[:, :, :3] + \
-               torch.ones(img.shape[0], img.shape[1], 3, device="cuda:0") * (1 - img[:, :, 3:4])
+               torch.ones(img.shape[0], img.shape[1], 3, device=device) * (1 - img[:, :, 3:4])
     img = img[:, :, :3]
     save_image(img, f"{experiment_dir}/{font}_{word}_{letter}.png")