Added examples

app.py

@@ -19,6 +19,31 @@ WHITE = 255
 COLORS = ["red", "blue", "green", "orange", "purple", "turquoise", "olive"]
 
 
+PROMPT1 = "3D Pixar animation of a cute unicorn and a pink hedgehog and a nerdy owl traveling in a magical forest" 
+PROMPT2 = "science fiction movie poster with an astronaut and a robot and a green alien and a spaceship"
+PROMPT3 = "a golden retriever and a german shepherd and a boston terrier and an english bulldog and a border collie in a pool"
+EXAMPLE_BOXES = {
+    PROMPT1 : [
+        [0.35, 0.4, 0.65, 0.9],
+        [0, 0.6, 0.3, 0.9],
+        [0.7, 0.55, 1, 0.85]
+    ],
+    PROMPT2: [
+        [0.4, 0.45, 0.6, 0.95],
+        [0.2, 0.3, 0.4, 0.85],
+        [0.6, 0.3, 0.8, 0.85],
+        [0.1, 0, 0.9, 0.3]
+    ],
+    PROMPT3: [
+        [0, 0.5, 0.2, 0.8],
+        [0.2, 0.2, 0.4, 0.5],
+        [0.4, 0.5, 0.6, 0.8],
+        [0.6, 0.2, 0.8, 0.5],
+        [0.8, 0.5, 1, 0.8]
+    ],
+}
+
+
 def inference(
     boxes,
     prompts,
@@ -90,7 +115,7 @@ def generate(
     loss_threshold,
     num_guidance_steps,
     seed,
-    boxes
+    boxes,
 ):
     subject_token_indices = convert_token_indices(subject_token_indices, nested=True)
     if len(boxes) != len(subject_token_indices):
@@ -157,6 +182,37 @@ def clear(batch_size):
     return [[], None, None, None]
 
 
+def generate_example(
+    prompt,
+    subject_token_indices,
+    filter_token_indices,
+    num_tokens,
+    init_step_size,
+    final_step_size,
+    num_clusters_per_subject,
+    cross_loss_scale,
+    self_loss_scale,
+    classifier_free_guidance_scale,
+    batch_size,
+    num_iterations,
+    loss_threshold,
+    num_guidance_steps,
+    seed,
+):
+    layers = []
+    boxes = EXAMPLE_BOXES[prompt]
+    for box in boxes:
+        layers.append(draw_boxes([box]))
+
+    sketchpad = {'layers': layers}
+    layout_images = draw_boxes(boxes)
+    out_images = generate(prompt, subject_token_indices, filter_token_indices, num_tokens, init_step_size,
+        final_step_size, num_clusters_per_subject, cross_loss_scale, self_loss_scale, classifier_free_guidance_scale,
+        batch_size, num_iterations, loss_threshold, num_guidance_steps, seed, boxes)
+
+    return boxes, sketchpad, layout_image, out_images
+
+
 def main():
     css = """
     #paper-info a {
@@ -279,9 +335,9 @@ def main():
                         </div>
                     """
                     gr.HTML(description)
-                    batch_size = gr.Slider(minimum=1, maximum=5, step=1, value=1, label="Number of samples (currently limited to one sample)")
-                    init_step_size = gr.Slider(minimum=0, maximum=50, step=0.5, value=25, label="Initial step size")
-                    final_step_size = gr.Slider(minimum=0, maximum=20, step=0.5, value=10, label="Final step size")
+                    batch_size = gr.Slider(minimum=1, maximum=5, step=1, value=1, label="Number of samples (limited to one sample on current space)")
+                    init_step_size = gr.Slider(minimum=0, maximum=50, step=0.5, value=18, label="Initial step size")
+                    final_step_size = gr.Slider(minimum=0, maximum=20, step=0.5, value=5, label="Final step size")
                     num_clusters_per_subject = gr.Slider(minimum=0, maximum=5, step=0.5, value=3, label="Number of clusters per subject")
                     cross_loss_scale = gr.Slider(minimum=0, maximum=2, step=0.1, value=1, label="Cross-attention loss scale factor")
                     self_loss_scale = gr.Slider(minimum=0, maximum=2, step=0.1, value=1, label="Self-attention loss scale factor")
@@ -320,22 +376,41 @@ def main():
                 queue=True,
             )
 
-        #with gr.Column():
-        #    gr.Examples(
-        #        examples=[
-        #            [
-        #                [[0.35, 0.4, 0.65, 0.9], [0, 0.6, 0.3, 0.9], [0.7, 0.55, 1, 0.85]],
-        #                "3D Pixar animation of a cute unicorn and a pink hedgehog and a nerdy owl traveling in a magical forest",
-        #                "7,8,17;11,12,17;15,16,17",
-        #                "5,6,9,10,13,14,18,19",
-        #                286,
-        #            ],
-        #        ],
-        #        inputs=[boxes, prompt, subject_token_indices, filter_token_indices, seed],
-        #        outputs=None,
-        #        fn=None,
-        #        cache_examples=False,
-        #    )
+        with gr.Column():
+            gr.Examples(
+                examples=[
+                    [
+                        "3D Pixar animation of a cute unicorn and a pink hedgehog and a nerdy owl traveling in a magical forest",
+                        "7,8,17;11,12,17;15,16,17", "5,6,9,10,13,14,18,19", "21",
+                        25, 10, 3, 1, 1,
+                        7.5, 1, 5, 0.2, 15,
+                        286,
+                    ],
+                    [
+                        "science fiction movie poster with an astronaut and a robot and a green alien and a spaceship",
+                        "7;10;13,14;17", "5,6,8,9,11,12,15,16", "17",
+                        18, 5, 3, 1, 1,
+                        7.5, 1, 5, 0.2, 15,
+                        216,
+                    ],
+                    [
+                        "a golden retriever and a german shepherd and a boston terrier and an english bulldog and a border collie in a pool",
+                        "2,3;6,7;10,11;14,15;18,19", "1,4,5,8,9,12,13,16,17,20,21", "22",
+                        18, 5, 3, 1, 1,
+                        7.5, 1, 5, 0.2, 15,
+                        156,
+                    ],
+                ],
+                fn=generate_example,
+                inputs=[
+                    prompt, subject_token_indices, filter_token_indices, num_tokens,
+                    init_step_size, final_step_size, num_clusters_per_subject, cross_loss_scale, self_loss_scale,
+                    classifier_free_guidance_scale, batch_size, num_iterations, loss_threshold, num_guidance_steps,
+                    seed,
+                ],
+                outputs=[boxes, sketchpad, layout_image, out_images],
+                cache_examples=True,
+            )
         description = """<p> The source code of this demo is based on the <a href="https://huggingface.co/spaces/gligen/demo/tree/main">GLIGEN demo</a>.</p>"""
         gr.HTML(description)