cast image to numpy for gif

app.py

@@ -160,7 +160,7 @@ def init_shapes(svg_path, trainable: Mapping[str, bool]):
 def run_main_ex(word, semantic_concept, num_steps, seed):
     prompt_suffix = "minimal flat 2d vector. lineal color. trending on artstation"
     font_name = "ArefRuqaa"
-    return list(next(run_main_app(semantic_concept, word, prompt_suffix, font_name, num_steps, seed, 100, 201, 30, 0.5, 0)))
+    return list(next(run_main_app(semantic_concept, word, prompt_suffix, font_name, num_steps, seed, 100, 201, 30, 0.5, 1)))
                         
 def run_main_app(semantic_concept, word, prompt_suffix, font_name, num_steps, seed, dist_loss_weight, pixel_dist_kernel_blur, pixel_dist_sigma, angeles_w, example=0):
     
@@ -222,7 +222,7 @@ def run_main_app(semantic_concept, word, prompt_suffix, font_name, num_steps, se
         img = img[:, :, 3:4] * img[:, :, :3] + torch.ones(img.shape[0], img.shape[1], 3, device=device) * (
                     1 - img[:, :, 3:4])
         img = img[:, :, :3]
-        gif_frames += [img]
+        gif_frames += [img.detach().cpu().numpy()]
 
         
         filename = os.path.join(cfg.experiment_dir, "video-svg", f"iter{step:04d}.svg")