loopback moved to scripts, added support for multiple batches, changed to honor save grids and how grids in web setting

modules/img2img.py

@@ -11,10 +11,9 @@ from modules.ui import plaintext_to_html
 import modules.images as images
 import modules.scripts
 
-def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init_img_with_mask, init_mask, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, denoising_strength_change_factor: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
+def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init_img_with_mask, init_mask, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
     is_inpaint = mode == 1
-    is_loopback = mode == 2
+    is_upscale = mode == 2
-    is_upscale = mode == 3
 
     if is_inpaint:
         if mask_mode == 0:
@@ -61,46 +60,10 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init
         denoising_strength=denoising_strength,
         inpaint_full_res=inpaint_full_res,
         inpainting_mask_invert=inpainting_mask_invert,
-        extra_generation_params={
-            "Denoising strength change factor": (denoising_strength_change_factor if is_loopback else None)
-        }
     )
     print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
 
-    if is_loopback:
+    if is_upscale:
-        output_images, info = None, None
-        history = []
-        initial_seed = None
-        initial_info = None
-
-        state.job_count = n_iter
-
-        for i in range(n_iter):
-            p.n_iter = 1
-            p.batch_size = 1
-            p.do_not_save_grid = True
-
-            state.job = f"Batch {i + 1} out of {n_iter}"
-            processed = process_images(p)
-
-            if initial_seed is None:
-                initial_seed = processed.seed
-                initial_info = processed.info
-            
-            init_img = processed.images[0]
-
-            p.init_images = [init_img]
-            p.seed = processed.seed + 1
-            p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
-            history.append(processed.images[0])
-
-        grid = images.image_grid(history, batch_size, rows=1)
-
-        images.save_image(grid, p.outpath_grids, "grid", initial_seed, prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
-
-        processed = Processed(p, history, initial_seed, initial_info)
-
-    elif is_upscale:
         initial_info = None
 
         processing.fix_seed(p)

modules/ui.py

@@ -387,7 +387,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel'):
                 with gr.Group():
-                    switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'Loopback', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
+                    switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
                     init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil")
                     init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False, image_mode="RGBA")
                     init_mask = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
@@ -421,7 +421,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                 with gr.Group():
                     cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
                     denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75)
-                    denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, visible=False)
 
                 with gr.Group():
                     width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
@@ -455,8 +454,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
             def apply_mode(mode, uploadmask):
                 is_classic = mode == 0
                 is_inpaint = mode == 1
-                is_loopback = mode == 2
+                is_upscale = mode == 2
-                is_upscale = mode == 3
 
                 return {
                     init_img: gr_show(not is_inpaint or (is_inpaint and uploadmask == 1)),
@@ -466,12 +464,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     mask_mode: gr_show(is_inpaint),
                     mask_blur: gr_show(is_inpaint),
                     inpainting_fill: gr_show(is_inpaint),
-                    batch_size: gr_show(not is_loopback),
                     sd_upscale_upscaler_name: gr_show(is_upscale),
                     sd_upscale_overlap: gr_show(is_upscale),
                     inpaint_full_res: gr_show(is_inpaint),
                     inpainting_mask_invert: gr_show(is_inpaint),
-                    denoising_strength_change_factor: gr_show(is_loopback),
                     img2img_interrogate: gr_show(not is_inpaint),
                 }
 
@@ -486,12 +482,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     mask_mode,
                     mask_blur,
                     inpainting_fill,
-                    batch_size,
                     sd_upscale_upscaler_name,
                     sd_upscale_overlap,
                     inpaint_full_res,
                     inpainting_mask_invert,
-                    denoising_strength_change_factor,
                     img2img_interrogate,
                 ]
             )
@@ -532,7 +526,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
                     batch_size,
                     cfg_scale,
                     denoising_strength,
-                    denoising_strength_change_factor,
                     seed,
                     subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
                     height,

script.js

@@ -13,7 +13,6 @@ titles = {
     "Seed": "A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result",
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
-    "Loopback": "Process an image, use it as an input, repeat. Batch count determins number of iterations.",
     "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
 
     "Just resize": "Resize image to target resolution. Unless height and width match, you will get incorrect aspect ratio.",
@@ -58,6 +57,9 @@ titles = {
 
     "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
     "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
+
+    "Loopback": "Process an image, use it as an input, repeat.",
+    "Loops": "How many times to repeat processing an image and using it as input for the next iteration",
 }
 
 function gradioApp(){

scripts/loopback.py

@@ -0,0 +1,78 @@
+import numpy as np
+from tqdm import trange
+
+import modules.scripts as scripts
+import gradio as gr
+
+from modules import processing, shared, sd_samplers, images
+from modules.processing import Processed
+from modules.sd_samplers import samplers
+from modules.shared import opts, cmd_opts, state
+
+class Script(scripts.Script):
+    def title(self):
+        return "Loopback"
+
+    def show(self, is_img2img):
+        return is_img2img
+
+    def ui(self, is_img2img):
+        loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4)
+        denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1)
+
+        return [loops, denoising_strength_change_factor]
+
+    def run(self, p, loops, denoising_strength_change_factor):
+        processing.fix_seed(p)
+        batch_count = p.n_iter
+        p.extra_generation_params = {
+            "Denoising strength change factor": denoising_strength_change_factor,
+        }
+
+        p.batch_size = 1
+        p.n_iter = 1
+
+        output_images, info = None, None
+        initial_seed = None
+        initial_info = None
+
+        grids = []
+        all_images = []
+        state.job_count = loops * batch_count
+
+        for n in range(batch_count):
+            history = []
+
+            for i in range(loops):
+                p.n_iter = 1
+                p.batch_size = 1
+                p.do_not_save_grid = True
+
+                state.job = f"Iteration {i + 1}/{loops}, batch {n + 1}/{batch_count}"
+
+                processed = processing.process_images(p)
+
+                if initial_seed is None:
+                    initial_seed = processed.seed
+                    initial_info = processed.info
+
+                init_img = processed.images[0]
+
+                p.init_images = [init_img]
+                p.seed = processed.seed + 1
+                p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
+                history.append(processed.images[0])
+
+            grid = images.image_grid(history, rows=1)
+            if opts.grid_save:
+                images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
+
+            grids.append(grid)
+            all_images += history
+
+        if opts.return_grid:
+            all_images = grids + all_images
+
+        processed = Processed(p, all_images, initial_seed, initial_info)
+
+        return processed