explain code

Author: lllyasviel

Diff for: gradio_canny2image.py

@@ -49,7 +49,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_depth2image.py

@@ -51,7 +51,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_fake_scribble2image.py

@@ -55,7 +55,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_hed2image.py

@@ -51,7 +51,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_hough2image.py

@@ -51,7 +51,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_normal2image.py

@@ -51,7 +51,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_pose2image.py

@@ -51,7 +51,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_scribble2image.py

@@ -46,7 +46,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_scribble2image_interactive.py

@@ -46,7 +46,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,

Diff for: gradio_seg2image.py

@@ -50,7 +50,7 @@ def process(input_image, prompt, a_prompt, n_prompt, num_samples, image_resoluti
         if config.save_memory:
             model.low_vram_shift(is_diffusing=True)
 
-        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)
+        model.control_scales = [strength * (0.825 ** float(12 - i)) for i in range(13)] if guess_mode else ([strength] * 13)  # Magic number. IDK why. Perhaps because 0.825**12<0.01 but 0.826**12>0.01
         samples, intermediates = ddim_sampler.sample(ddim_steps, num_samples,
                                                      shape, cond, verbose=False, eta=eta,
                                                      unconditional_guidance_scale=scale,