Add an option for faster low quality previews

modules/sd_samplers.py

@@ -106,7 +106,16 @@ def setup_img2img_steps(p, steps=None):
     return steps, t_enc
 
 
-def single_sample_to_image(sample):
+def single_sample_to_image(sample, approximation=False):
+    if approximation:
+        # https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/2
+        coefs = torch.tensor(
+            [[ 0.298,  0.207,  0.208],
+             [ 0.187,  0.286,  0.173],
+             [-0.158,  0.189,  0.264],
+             [-0.184, -0.271, -0.473]]).to(sample.device)
+        x_sample = torch.einsum("lxy,lr -> rxy", sample, coefs)
+    else:
         x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0]
     x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)
     x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
@@ -114,12 +123,12 @@ def single_sample_to_image(sample):
     return Image.fromarray(x_sample)
 
 
-def sample_to_image(samples, index=0):
+def sample_to_image(samples, index=0, approximation=False):
-    return single_sample_to_image(samples[index])
+    return single_sample_to_image(samples[index], approximation)
 
 
-def samples_to_image_grid(samples):
+def samples_to_image_grid(samples, approximation=False):
-    return images.image_grid([single_sample_to_image(sample) for sample in samples])
+    return images.image_grid([single_sample_to_image(sample, approximation) for sample in samples])
 
 
 def store_latent(decoded):
@@ -127,7 +136,7 @@ def store_latent(decoded):
 
     if opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
         if not shared.parallel_processing_allowed:
-            shared.state.current_image = sample_to_image(decoded)
+            shared.state.current_image = sample_to_image(decoded, approximation=opts.show_progress_approximate)
 
 
 class InterruptedException(BaseException):

modules/shared.py

@@ -212,9 +212,9 @@ class State:
 
         import modules.sd_samplers
         if opts.show_progress_grid:
-            self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent)
+            self.current_image = modules.sd_samplers.samples_to_image_grid(self.current_latent, approximation=opts.show_progress_approximate)
         else:
-            self.current_image = modules.sd_samplers.sample_to_image(self.current_latent)
+            self.current_image = modules.sd_samplers.sample_to_image(self.current_latent, approximation=opts.show_progress_approximate)
 
         self.current_image_sampling_step = self.sampling_step
 
@@ -391,6 +391,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
 options_templates.update(options_section(('ui', "User interface"), {
     "show_progressbar": OptionInfo(True, "Show progressbar"),
     "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set to 0 to disable. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
+    "show_progress_approximate": OptionInfo(False, "Calculate small previews using fast linear approximation instead of VAE"),
     "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
     "return_grid": OptionInfo(True, "Show grid in results for web"),
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),