fix crash in generate._transparency_check_and_warning()

This reverts commit 5f42d08945.

This fix was intended to solve issue #939, in which ESRGAN generates
dark images when upscaling 4X on certain GTX cards. However, the fix
apparently causes conflicts with some versions of the ESRGAN library,
and this fix will have to wait until after release of 2.0.

backend/invoke_ai_web_server.py

@@ -53,17 +53,14 @@ class InvokeAIWebServer:
         cors_allowed_origins = [
             'http://127.0.0.1:5173',
             'http://localhost:5173',
+            'http://localhost:9090'
         ]
         additional_allowed_origins = (
             opt.cors if opt.cors else []
         )  # additional CORS allowed origins
-        if self.host == '127.0.0.1':
-            cors_allowed_origins.extend(
-                [
-                    f'http://{self.host}:{self.port}',
-                    f'http://localhost:{self.port}',
-                ]
-            )
+        cors_allowed_origins.append(f'http://{self.host}:{self.port}')
+        if self.host == '127.0.0.1' or self.host == '0.0.0.0':
+            cors_allowed_origins.append(f'http://localhost:{self.port}')
         cors_allowed_origins = (
             cors_allowed_origins + additional_allowed_origins
         )

docs/features/IMG2IMG.md

@@ -10,18 +10,39 @@ top of the image you provide, preserving the original's basic shape and layout.
 the `--init_img` option as shown here:
 
 ```commandline
-dream> "waterfall and rainbow" --init_img=./init-images/crude_drawing.png --strength=0.5 -s100 -n4
+tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85
 ```
 
+This will take the original image shown here:
+
+<img src="https://user-images.githubusercontent.com/50542132/193946000-c42a96d8-5a74-4f8a-b4c3-5213e6cadcce.png" width=350>
+                                                                                                               
+and generate a new image based on it as shown here:
+
+<img src="https://user-images.githubusercontent.com/111189/194135515-53d4c060-e994-4016-8121-7c685e281ac9.png" width=350>
+
 The `--init_img (-I)` option gives the path to the seed picture. `--strength (-f)` controls how much
 the original will be modified, ranging from `0.0` (keep the original intact), to `1.0` (ignore the
-original completely). The default is `0.75`, and ranges from `0.25-0.75` give interesting results.
+original completely). The default is `0.75`, and ranges from `0.25-0.90` give interesting results. 
+Other relevant options include `-C` (classification free guidance scale), and `-s` (steps). Unlike `txt2img`, 
+adding steps will continuously change the resulting image and it will not converge.
 
 You may also pass a `-v<variation_amount>` option to generate `-n<iterations>` count variants on
 the original image. This is done by passing the first generated image
 back into img2img the requested number of times. It generates
 interesting variants.
 
+Note that the prompt makes a big difference. For example, this slight variation on the prompt produces
+a very different image:
+
+`photograph of a tree on a hill with a river`
+
+<img src="https://user-images.githubusercontent.com/111189/194135220-16b62181-b60c-4248-8989-4834a8fd7fbd.png" width=350>
+
+(When designing prompts, think about how the images scraped from the internet were captioned. Very few photographs will
+be labeled "photograph" or "photorealistic." They will, however, be captioned with the publication, photographer, camera
+model, or film settings.)
+
 If the initial image contains transparent regions, then Stable Diffusion will only draw within the
 transparent regions, a process called "inpainting". However, for this to work correctly, the color
 information underneath the transparent needs to be preserved, not erased.
@@ -29,6 +50,14 @@ information underneath the transparent needs to be preserved, not erased.
 More details can be found here:
 [Creating Transparent Images For Inpainting](./INPAINTING.md#creating-transparent-regions-for-inpainting)
 
+**IMPORTANT ISSUE** `img2img` does not work properly on initial images smaller than 512x512. Please scale your
+image to at least 512x512 before using it. Larger images are not a problem, but may run out of VRAM on your
+GPU card. To fix this, use the --fit option, which downscales the initial image to fit within the box specified
+by width x height:
+~~~
+tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit
+~~~
+
 ## How does it actually work, though?
 
 The main difference between `img2img` and `prompt2img` is the starting point. While `prompt2img` always starts with pure 

docs/features/PROMPTS.md

@@ -114,7 +114,7 @@ is depth there, so the enclosing frame is actually a cube.
 
 ### "blue sphere:0.25 red cube:0.75 hybrid"
 
-<img src="../assets/prompt-blending/blue-sphere:0.25-red-cube:0.75-hybrid.png" width=256>
+<img src="../assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png" width=256>
 
 Now that's interesting. We get neither a blue sphere nor a red cube,
 but a red sphere embedded in a brick wall, which represents a melding
@@ -123,14 +123,14 @@ representations. Where is Ludwig Wittgenstein when you need him?
 
 ### "blue sphere:0.75 red cube:0.25 hybrid"
 
-<img src="../assets/prompt-blending/blue-sphere:0.75-red-cube:0.25-hybrid.png" width=256>
+<img src="../assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png" width=256>
 
 Definitely more blue-spherey. The cube is gone entirely, but it's
 really cool abstract art.
 
 ### "blue sphere:0.5 red cube:0.5 hybrid"
 
-<img src="../assets/prompt-blending/blue-sphere:0.5-red-cube:0.5-hybrid.png" width=256>
+<img src="../assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png" width=256>
 
 Whoa...! I see blue and red, but no spheres or cubes. Is the word
 "hybrid" summoning up the concept of some sort of scifi creature?
@@ -138,7 +138,7 @@ Let's find out.
 
 ### "blue sphere:0.5 red cube:0.5"
 
-<img src="../assets/prompt-blending/blue-sphere:0.5-red-cube:0.5.png" width=256>
+<img src="../assets/prompt-blending/blue-sphere-0.5-red-cube-0.5.png" width=256>
 
 Indeed, removing the word "hybrid" produces an image that is more like
 what we'd expect.

frontend/dist/index.html

@@ -6,7 +6,7 @@
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
   <title>InvokeAI - A Stable Diffusion Toolkit</title>
   <link rel="shortcut icon" type="icon" href="/assets/favicon.0d253ced.ico" />
-  <script type="module" crossorigin src="/assets/index.d9916e7a.js"></script>
+  <script type="module" crossorigin src="/assets/index.d6e02692.js"></script>
   <link rel="stylesheet" href="/assets/index.853a336f.css">
 </head>
 

frontend/package.json

@@ -23,6 +23,7 @@
     "react": "^18.2.0",
     "react-dom": "^18.2.0",
     "react-dropzone": "^14.2.2",
+    "react-hotkeys-hook": "^3.4.7",
     "react-icons": "^4.4.0",
     "react-redux": "^8.0.2",
     "redux-persist": "^6.0.0",

frontend/src/features/gallery/CurrentImageButtons.tsx

@@ -19,6 +19,8 @@ import { MdDelete, MdFace, MdHd, MdImage, MdInfo } from 'react-icons/md';
 import InvokePopover from './InvokePopover';
 import UpscaleOptions from '../options/AdvancedOptions/Upscale/UpscaleOptions';
 import FaceRestoreOptions from '../options/AdvancedOptions/FaceRestore/FaceRestoreOptions';
+import { useHotkeys } from 'react-hotkeys-hook';
+import { useToast } from '@chakra-ui/react';
 
 const systemSelector = createSelector(
   (state: RootState) => state.system,
@@ -54,6 +56,8 @@ const CurrentImageButtons = ({
 }: CurrentImageButtonsProps) => {
   const dispatch = useAppDispatch();
 
+  const toast = useToast();
+
   const intermediateImage = useAppSelector(
     (state: RootState) => state.gallery.intermediateImage
   );
@@ -71,19 +75,163 @@ const CurrentImageButtons = ({
 
   const handleClickUseAsInitialImage = () =>
     dispatch(setInitialImagePath(image.url));
+  useHotkeys(
+    'shift+i',
+    () => {
+      if (image) {
+        handleClickUseAsInitialImage();
+        toast({
+          title: 'Sent To Image To Image',
+          status: 'success',
+          duration: 2500,
+          isClosable: true,
+        });
+      } else {
+        toast({
+          title: 'No Image Loaded',
+          description: 'No image found to send to image to image module.',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [image]
+  );
 
   const handleClickUseAllParameters = () =>
     dispatch(setAllParameters(image.metadata));
+  useHotkeys(
+    'a',
+    () => {
+      if (['txt2img', 'img2img'].includes(image?.metadata?.image?.type)) {
+        handleClickUseAllParameters();
+        toast({
+          title: 'Parameters Set',
+          status: 'success',
+          duration: 2500,
+          isClosable: true,
+        });
+      } else {
+        toast({
+          title: 'Parameters Not Set',
+          description: 'No metadata found for this image.',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [image]
+  );
 
   // Non-null assertion: this button is disabled if there is no seed.
   // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
   const handleClickUseSeed = () => dispatch(setSeed(image.metadata.image.seed));
+  useHotkeys(
+    's',
+    () => {
+      if (image?.metadata?.image?.seed) {
+        handleClickUseSeed();
+        toast({
+          title: 'Seed Set',
+          status: 'success',
+          duration: 2500,
+          isClosable: true,
+        });
+      } else {
+        toast({
+          title: 'Seed Not Set',
+          description: 'Could not find seed for this image.',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [image]
+  );
+
   const handleClickUpscale = () => dispatch(runESRGAN(image));
+  useHotkeys(
+    'u',
+    () => {
+      if (
+        isESRGANAvailable &&
+        Boolean(!intermediateImage) &&
+        isConnected &&
+        !isProcessing &&
+        upscalingLevel
+      ) {
+        handleClickUpscale();
+      } else {
+        toast({
+          title: 'Upscaling Failed',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [
+      image,
+      isESRGANAvailable,
+      intermediateImage,
+      isConnected,
+      isProcessing,
+      upscalingLevel,
+    ]
+  );
 
   const handleClickFixFaces = () => dispatch(runGFPGAN(image));
+  useHotkeys(
+    'r',
+    () => {
+      if (
+        isGFPGANAvailable &&
+        Boolean(!intermediateImage) &&
+        isConnected &&
+        !isProcessing &&
+        gfpganStrength
+      ) {
+        handleClickFixFaces();
+      } else {
+        toast({
+          title: 'Face Restoration Failed',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [
+      image,
+      isGFPGANAvailable,
+      intermediateImage,
+      isConnected,
+      isProcessing,
+      gfpganStrength,
+    ]
+  );
 
   const handleClickShowImageDetails = () =>
     setShouldShowImageDetails(!shouldShowImageDetails);
+  useHotkeys(
+    'i',
+    () => {
+      if (image) {
+        handleClickShowImageDetails();
+      } else {
+        toast({
+          title: 'Failed to load metadata',
+          status: 'error',
+          duration: 2500,
+          isClosable: true,
+        });
+      }
+    },
+    [image, shouldShowImageDetails]
+  );
 
   return (
     <div className="current-image-options">

frontend/src/features/gallery/CurrentImageDisplay.scss

@@ -67,6 +67,44 @@
   }
 }
 
+.current-image-next-prev-buttons {
+  position: absolute;
+  top: 0;
+  left: 0;
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  width: calc(100% - 2rem);
+  padding: 0.5rem;
+  margin-left: 1rem;
+  z-index: 1;
+  height: calc($app-metadata-height - 1rem);
+  pointer-events: none;
+}
+
+.next-prev-button-trigger-area {
+  width: 7rem;
+  height: 100%;
+  display: flex;
+  align-items: center;
+  pointer-events: auto;
+
+  &.prev-button-trigger-area {
+    justify-content: flex-start;
+  }
+
+  &.next-button-trigger-area {
+    justify-content: flex-end;
+  }
+}
+
+.next-prev-button {
+  font-size: 5rem;
+  fill: var(--text-color-secondary);
+  filter: drop-shadow(0 0 1rem var(--text-color-secondary));
+  opacity: 70%;
+}
+
 .current-image-metadata-viewer {
   border-radius: 0.5rem;
   position: absolute;

frontend/src/features/gallery/CurrentImageDisplay.tsx

@@ -1,15 +1,21 @@
-import { Image } from '@chakra-ui/react';
-import { useAppSelector } from '../../app/store';
+import { IconButton, Image } from '@chakra-ui/react';
+import { useAppDispatch, useAppSelector } from '../../app/store';
 import { RootState } from '../../app/store';
 import { useState } from 'react';
 import ImageMetadataViewer from './ImageMetadataViewer';
 import CurrentImageButtons from './CurrentImageButtons';
 import { MdPhoto } from 'react-icons/md';
+import { FaAngleLeft, FaAngleRight } from 'react-icons/fa';
+import { selectNextImage, selectPrevImage } from './gallerySlice';
 
 /**
  * Displays the current image if there is one, plus associated actions.
  */
 const CurrentImageDisplay = () => {
+  const dispatch = useAppDispatch();
+  const [shouldShowNextPrevButtons, setShouldShowNextPrevButtons] =
+    useState<boolean>(false);
+
   const { currentImage, intermediateImage } = useAppSelector(
     (state: RootState) => state.gallery
   );
@@ -19,6 +25,22 @@ const CurrentImageDisplay = () => {
 
   const imageToDisplay = intermediateImage || currentImage;
 
+  const handleCurrentImagePreviewMouseOver = () => {
+    setShouldShowNextPrevButtons(true);
+  };
+
+  const handleCurrentImagePreviewMouseOut = () => {
+    setShouldShowNextPrevButtons(false);
+  };
+
+  const handleClickPrevButton = () => {
+    dispatch(selectPrevImage());
+  };
+
+  const handleClickNextButton = () => {
+    dispatch(selectNextImage());
+  };
+
   return imageToDisplay ? (
     <div className="current-image-display">
       <div className="current-image-tools">
@@ -40,6 +62,38 @@ const CurrentImageDisplay = () => {
             <ImageMetadataViewer image={imageToDisplay} />
           </div>
         )}
+        {!shouldShowImageDetails && (
+          <div className="current-image-next-prev-buttons">
+            <div
+              className="next-prev-button-trigger-area prev-button-trigger-area"
+              onMouseOver={handleCurrentImagePreviewMouseOver}
+              onMouseOut={handleCurrentImagePreviewMouseOut}
+            >
+              {shouldShowNextPrevButtons && (
+                <IconButton
+                  aria-label="Previous image"
+                  icon={<FaAngleLeft className="next-prev-button" />}
+                  variant="unstyled"
+                  onClick={handleClickPrevButton}
+                />
+              )}
+            </div>
+            <div
+              className="next-prev-button-trigger-area next-button-trigger-area"
+              onMouseOver={handleCurrentImagePreviewMouseOver}
+              onMouseOut={handleCurrentImagePreviewMouseOut}
+            >
+              {shouldShowNextPrevButtons && (
+                <IconButton
+                  aria-label="Next image"
+                  icon={<FaAngleRight className="next-prev-button" />}
+                  variant="unstyled"
+                  onClick={handleClickNextButton}
+                />
+              )}
+            </div>
+          </div>
+        )}
       </div>
     </div>
   ) : (

frontend/src/features/gallery/DeleteImageModal.tsx

@@ -27,6 +27,7 @@ import { deleteImage } from '../../app/socketio/actions';
 import { RootState } from '../../app/store';
 import { setShouldConfirmOnDelete, SystemState } from '../system/systemSlice';
 import * as InvokeAI from '../../app/invokeai';
+import { useHotkeys } from 'react-hotkeys-hook';
 
 interface DeleteImageModalProps {
   /**
@@ -67,6 +68,14 @@ const DeleteImageModal = forwardRef(
       onClose();
     };
 
+    useHotkeys(
+      'del',
+      () => {
+        shouldConfirmOnDelete ? onOpen() : handleDelete();
+      },
+      [image, shouldConfirmOnDelete]
+    );
+
     const handleChangeShouldConfirmOnDelete = (
       e: ChangeEvent<HTMLInputElement>
     ) => dispatch(setShouldConfirmOnDelete(!e.target.checked));

frontend/src/features/gallery/ImageGallery.tsx

@@ -1,8 +1,10 @@
 import { Button } from '@chakra-ui/react';
+import { useHotkeys } from 'react-hotkeys-hook';
 import { MdPhotoLibrary } from 'react-icons/md';
 import { requestImages } from '../../app/socketio/actions';
 import { RootState, useAppDispatch } from '../../app/store';
 import { useAppSelector } from '../../app/store';
+import { selectNextImage, selectPrevImage } from './gallerySlice';
 import HoverableImage from './HoverableImage';
 
 /**
@@ -25,6 +27,22 @@ const ImageGallery = () => {
     dispatch(requestImages());
   };
 
+  useHotkeys(
+    'left',
+    () => {
+      dispatch(selectPrevImage());
+    },
+    []
+  );
+
+  useHotkeys(
+    'right',
+    () => {
+      dispatch(selectNextImage());
+    },
+    []
+  );
+
   return (
     <div className="image-gallery-container">
       {images.length ? (

frontend/src/features/gallery/gallerySlice.ts

@@ -1,6 +1,6 @@
 import { createSlice } from '@reduxjs/toolkit';
 import type { PayloadAction } from '@reduxjs/toolkit';
-import { clamp } from 'lodash';
+import _, { clamp } from 'lodash';
 import * as InvokeAI from '../../app/invokeai';
 
 export interface GalleryState {
@@ -85,6 +85,32 @@ export const gallerySlice = createSlice({
     clearIntermediateImage: (state) => {
       state.intermediateImage = undefined;
     },
+    selectNextImage: (state) => {
+      const { images, currentImage } = state;
+      if (currentImage) {
+        const currentImageIndex = images.findIndex(
+          (i) => i.uuid === currentImage.uuid
+        );
+        if (_.inRange(currentImageIndex, 0, images.length)) {
+          const newCurrentImage = images[currentImageIndex + 1];
+          state.currentImage = newCurrentImage;
+          state.currentImageUuid = newCurrentImage.uuid;
+        }
+      }
+    },
+    selectPrevImage: (state) => {
+      const { images, currentImage } = state;
+      if (currentImage) {
+        const currentImageIndex = images.findIndex(
+          (i) => i.uuid === currentImage.uuid
+        );
+        if (_.inRange(currentImageIndex, 1, images.length + 1)) {
+          const newCurrentImage = images[currentImageIndex - 1];
+          state.currentImage = newCurrentImage;
+          state.currentImageUuid = newCurrentImage.uuid;
+        }
+      }
+    },
     addGalleryImages: (
       state,
       action: PayloadAction<{
@@ -122,6 +148,8 @@ export const {
   setCurrentImage,
   addGalleryImages,
   setIntermediateImage,
+  selectNextImage,
+  selectPrevImage,
 } = gallerySlice.actions;
 
 export default gallerySlice.reducer;

frontend/src/features/options/AdvancedOptions/Seed/SeedOptions.tsx

@@ -18,6 +18,8 @@ const SeedOptions = () => {
       </Flex>
       <Flex gap={2}>
         <Threshold />
+      </Flex>
+      <Flex gap={2}>
         <Perlin />
       </Flex>
     </Flex>

frontend/src/features/options/ProcessButtons/CancelButton.tsx

@@ -4,12 +4,23 @@ import { cancelProcessing } from '../../../app/socketio/actions';
 import { useAppDispatch, useAppSelector } from '../../../app/store';
 import IAIIconButton from '../../../common/components/IAIIconButton';
 import { systemSelector } from '../../../common/hooks/useCheckParameters';
+import { useHotkeys } from 'react-hotkeys-hook';
 
 export default function CancelButton() {
   const dispatch = useAppDispatch();
   const { isProcessing, isConnected } = useAppSelector(systemSelector);
   const handleClickCancel = () => dispatch(cancelProcessing());
 
+  useHotkeys(
+    'shift+x',
+    () => {
+      if (isConnected || isProcessing) {
+        handleClickCancel();
+      }
+    },
+    [isConnected, isProcessing]
+  );
+
   return (
     <IAIIconButton
       icon={<MdCancel />}

frontend/src/features/options/PromptInput/PromptInput.tsx

@@ -1,5 +1,5 @@
 import { FormControl, Textarea } from '@chakra-ui/react';
-import { ChangeEvent, KeyboardEvent } from 'react';
+import { ChangeEvent, KeyboardEvent, useRef } from 'react';
 import { RootState, useAppDispatch, useAppSelector } from '../../../app/store';
 import { generateImage } from '../../../app/socketio/actions';
 
@@ -9,6 +9,7 @@ import { isEqual } from 'lodash';
 import useCheckParameters, {
   systemSelector,
 } from '../../../common/hooks/useCheckParameters';
+import { useHotkeys } from 'react-hotkeys-hook';
 
 export const optionsSelector = createSelector(
   (state: RootState) => state.options,
@@ -28,6 +29,7 @@ export const optionsSelector = createSelector(
  * Prompt input text area.
  */
 const PromptInput = () => {
+  const promptRef = useRef<HTMLTextAreaElement>(null);
   const { prompt } = useAppSelector(optionsSelector);
   const { isProcessing } = useAppSelector(systemSelector);
   const dispatch = useAppDispatch();
@@ -37,6 +39,24 @@ const PromptInput = () => {
     dispatch(setPrompt(e.target.value));
   };
 
+  useHotkeys(
+    'ctrl+enter',
+    () => {
+      if (isReady) {
+        dispatch(generateImage());
+      }
+    },
+    [isReady]
+  );
+
+  useHotkeys(
+    'alt+a',
+    () => {
+      promptRef.current?.focus();
+    },
+    []
+  );
+
   const handleKeyDown = (e: KeyboardEvent<HTMLTextAreaElement>) => {
     if (e.key === 'Enter' && e.shiftKey === false && isReady) {
       e.preventDefault();
@@ -60,6 +80,7 @@ const PromptInput = () => {
           onKeyDown={handleKeyDown}
           resize="vertical"
           height={30}
+          ref={promptRef}
         />
       </FormControl>
     </div>

frontend/src/features/options/optionsSlice.ts

@@ -246,7 +246,9 @@ export const optionsSlice = createSlice({
       if (steps) state.steps = steps;
       if (cfg_scale) state.cfgScale = cfg_scale;
       if (threshold) state.threshold = threshold;
+      if (typeof threshold === 'undefined') state.threshold = 0;
       if (perlin) state.perlin = perlin;
+      if (typeof perlin === 'undefined') state.perlin = 0;      
       if (typeof seamless === 'boolean') state.seamless = seamless;
       if (width) state.width = width;
       if (height) state.height = height;

frontend/src/features/system/HotkeysModal/HotkeysModal.scss

@@ -0,0 +1,53 @@
+@use '../../../styles/Mixins/' as *;
+
+.hotkeys-modal {
+  display: grid;
+  padding: 1rem;
+  background-color: var(--settings-modal-bg) !important;
+  row-gap: 1rem;
+  font-family: Inter;
+
+  h1 {
+    font-size: 1.2rem;
+    font-weight: bold;
+  }
+}
+
+.hotkeys-modal-items {
+  display: grid;
+  row-gap: 0.5rem;
+  max-height: 32rem;
+  overflow-y: scroll;
+  @include HideScrollbar;
+}
+
+.hotkey-modal-item {
+  display: grid;
+  grid-template-columns: auto max-content;
+  justify-content: space-between;
+  align-items: center;
+  background-color: var(--background-color);
+  padding: 0.5rem 1rem;
+  border-radius: 0.3rem;
+
+  .hotkey-info {
+    display: grid;
+
+    .hotkey-title {
+      font-weight: bold;
+    }
+
+    .hotkey-description {
+      font-size: 0.9rem;
+      color: var(--text-color-secondary);
+    }
+  }
+
+  .hotkey-key {
+    font-size: 0.8rem;
+    font-weight: bold;
+    border: 2px solid var(--settings-modal-bg);
+    padding: 0.2rem 0.5rem;
+    border-radius: 0.3rem;
+  }
+}

frontend/src/features/system/HotkeysModal/HotkeysModal.tsx

@@ -0,0 +1,98 @@
+import {
+  Modal,
+  ModalCloseButton,
+  ModalContent,
+  ModalOverlay,
+  useDisclosure,
+} from '@chakra-ui/react';
+import React, { cloneElement, ReactElement } from 'react';
+import HotkeysModalItem from './HotkeysModalItem';
+
+type HotkeysModalProps = {
+  /* The button to open the Settings Modal */
+  children: ReactElement;
+};
+
+export default function HotkeysModal({ children }: HotkeysModalProps) {
+  const {
+    isOpen: isHotkeyModalOpen,
+    onOpen: onHotkeysModalOpen,
+    onClose: onHotkeysModalClose,
+  } = useDisclosure();
+
+  const hotkeys = [
+    { title: 'Invoke', desc: 'Generate an image', hotkey: 'Ctrl+Enter' },
+    { title: 'Cancel', desc: 'Cancel image generation', hotkey: 'Shift+X' },
+    {
+      title: 'Set Seed',
+      desc: 'Use the seed of the current image',
+      hotkey: 'S',
+    },
+    {
+      title: 'Set Parameters',
+      desc: 'Use all parameters of the current image',
+      hotkey: 'A',
+    },
+    { title: 'Restore Faces', desc: 'Restore the current image', hotkey: 'R' },
+    { title: 'Upscale', desc: 'Upscale the current image', hotkey: 'U' },
+    {
+      title: 'Show Info',
+      desc: 'Show metadata info of the current image',
+      hotkey: 'I',
+    },
+    {
+      title: 'Send To Image To Image',
+      desc: 'Send the current image to Image to Image module',
+      hotkey: 'Shift+I',
+    },
+    { title: 'Delete Image', desc: 'Delete the current image', hotkey: 'Del' },
+    {
+      title: 'Focus Prompt',
+      desc: 'Focus the prompt input area',
+      hotkey: 'Alt+A',
+    },
+    {
+      title: 'Previous Image',
+      desc: 'Display the previous image in the gallery',
+      hotkey: 'Arrow left',
+    },
+    {
+      title: 'Next Image',
+      desc: 'Display the next image in the gallery',
+      hotkey: 'Arrow right',
+    },
+  ];
+
+  const renderHotkeyModalItems = () => {
+    const hotkeyModalItemsToRender: ReactElement[] = [];
+
+    hotkeys.forEach((hotkey, i) => {
+      hotkeyModalItemsToRender.push(
+        <HotkeysModalItem
+          key={i}
+          title={hotkey.title}
+          description={hotkey.desc}
+          hotkey={hotkey.hotkey}
+        />
+      );
+    });
+
+    return hotkeyModalItemsToRender;
+  };
+
+  return (
+    <>
+      {cloneElement(children, {
+        onClick: onHotkeysModalOpen,
+      })}
+      <Modal isOpen={isHotkeyModalOpen} onClose={onHotkeysModalClose}>
+        <ModalOverlay />
+        <ModalContent className="hotkeys-modal">
+          <ModalCloseButton />
+          <h1>Keyboard Shorcuts</h1>
+          <div className="hotkeys-modal-items">{renderHotkeyModalItems()}</div>
+        </ModalContent>
+      </Modal>
+    </>
+  );
+}

frontend/src/features/system/HotkeysModal/HotkeysModalItem.tsx

@@ -0,0 +1,20 @@
+import React from 'react';
+
+interface HotkeysModalProps {
+  hotkey: string;
+  title: string;
+  description?: string;
+}
+
+export default function HotkeysModalItem(props: HotkeysModalProps) {
+  const { title, hotkey, description } = props;
+  return (
+    <div className="hotkey-modal-item">
+      <div className="hotkey-info">
+        <p className="hotkey-title">{title}</p>
+        {description && <p className="hotkey-description">{description}</p>}
+      </div>
+      <div className="hotkey-key">{hotkey}</div>
+    </div>
+  );
+}

frontend/src/features/system/SettingsModal/SettingsModal.scss

@@ -2,6 +2,7 @@
 
 .settings-modal {
   background-color: var(--settings-modal-bg) !important;
+  font-family: Inter;
 
   .settings-modal-content {
     display: grid;

frontend/src/features/system/SiteHeader.scss

@@ -21,7 +21,7 @@
 
 .site-header-right-side {
   display: grid;
-  grid-template-columns: repeat(5, max-content);
+  grid-template-columns: repeat(6, max-content);
   align-items: center;
   column-gap: 0.5rem;
 }

frontend/src/features/system/SiteHeader.tsx

@@ -1,9 +1,11 @@
 import { IconButton, Link, useColorMode } from '@chakra-ui/react';
 
 import { FaSun, FaMoon, FaGithub } from 'react-icons/fa';
-import { MdHelp, MdSettings } from 'react-icons/md';
+import { MdHelp, MdKeyboard, MdSettings } from 'react-icons/md';
 
 import InvokeAILogo from '../../assets/images/logo.png';
+import HotkeysModal from './HotkeysModal/HotkeysModal';
+
 import SettingsModal from './SettingsModal/SettingsModal';
 import StatusIndicator from './StatusIndicator';
 
@@ -40,6 +42,16 @@ const SiteHeader = () => {
           />
         </SettingsModal>
 
+        <HotkeysModal>
+          <IconButton
+            aria-label="Hotkeys"
+            variant="link"
+            fontSize={24}
+            size={'sm'}
+            icon={<MdKeyboard />}
+          />
+        </HotkeysModal>
+
         <IconButton
           aria-label="Link to Github Issues"
           variant="link"

frontend/src/styles/index.scss

@@ -11,6 +11,7 @@
 @use '../features/system/SiteHeader.scss';
 @use '../features/system/StatusIndicator.scss';
 @use '../features/system/SettingsModal/SettingsModal.scss';
+@use '../features/system/HotkeysModal/HotkeysModal.scss';
 @use '../features/system/Console.scss';
 
 // options

frontend/yarn.lock

@@ -1582,6 +1582,11 @@ balanced-match@^1.0.0:
   resolved "https://registry.yarnpkg.com/balanced-match/-/balanced-match-1.0.2.tgz#e83e3a7e3f300b34cb9d87f615fa0cbf357690ee"
   integrity sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==
 
+base64id@2.0.0, base64id@~2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/base64id/-/base64id-2.0.0.tgz#2770ac6bc47d312af97a8bf9a634342e0cd25cb6"
+  integrity sha512-lGe34o6EHj9y3Kts9R4ZYs/Gr+6N7MCaMlIFA3F1R2O5/m7K06AxfSeO5530PEERE6/WyEg3lsuyw4GHlPZHog==
+
 binary-extensions@^2.0.0:
   version "2.2.0"
   resolved "https://registry.yarnpkg.com/binary-extensions/-/binary-extensions-2.2.0.tgz#75f502eeaf9ffde42fc98829645be4ea76bd9e2d"
@@ -2359,6 +2364,11 @@ hoist-non-react-statics@^3.3.0, hoist-non-react-statics@^3.3.1, hoist-non-react-
   dependencies:
     react-is "^16.7.0"
 
+hotkeys-js@3.9.4:
+  version "3.9.4"
+  resolved "https://registry.yarnpkg.com/hotkeys-js/-/hotkeys-js-3.9.4.tgz#ce1aa4c3a132b6a63a9dd5644fc92b8a9b9cbfb9"
+  integrity sha512-2zuLt85Ta+gIyvs4N88pCYskNrxf1TFv3LR9t5mdAZIX8BcgQQ48F2opUptvHa6m8zsy5v/a0i9mWzTrlNWU0Q==
+
 ignore@^5.2.0:
   version "5.2.0"
   resolved "https://registry.yarnpkg.com/ignore/-/ignore-5.2.0.tgz#6d3bac8fa7fe0d45d9f9be7bac2fc279577e345a"
@@ -2618,7 +2628,7 @@ normalize-path@^3.0.0, normalize-path@~3.0.0:
   resolved "https://registry.yarnpkg.com/normalize-path/-/normalize-path-3.0.0.tgz#0dcd69ff23a1c9b11fd0978316644a0388216a65"
   integrity sha512-6eZs5Ls3WtCisHWp9S2GUy8dqkpGi4BVSz3GaqiE6ezub0512ESztXUwUB6C6IKbQkY2Pnb/mD4WYojCRwcwLA==
 
-object-assign@^4.1.1:
+object-assign@^4, object-assign@^4.1.1:
   version "4.1.1"
   resolved "https://registry.yarnpkg.com/object-assign/-/object-assign-4.1.1.tgz#2109adc7965887cfc05cbbd442cac8bfbb360863"
   integrity sha512-rJgTQnkUnH1sFw8yT6VSU3zD3sWmu6sZhIseY8VX+GRu3P6F7Fu+JNDoXfklElbLJSnc3FUQHVe4cU5hj+BcUg==
@@ -2818,6 +2828,13 @@ react-focus-lock@^2.9.1:
     use-callback-ref "^1.3.0"
     use-sidecar "^1.1.2"
 
+react-hotkeys-hook@^3.4.7:
+  version "3.4.7"
+  resolved "https://registry.yarnpkg.com/react-hotkeys-hook/-/react-hotkeys-hook-3.4.7.tgz#e16a0a85f59feed9f48d12cfaf166d7df4c96b7a"
+  integrity sha512-+bbPmhPAl6ns9VkXkNNyxlmCAIyDAcWbB76O4I0ntr3uWCRuIQf/aRLartUahe9chVMPj+OEzzfk3CQSjclUEQ==
+  dependencies:
+    hotkeys-js "3.9.4"
+
 react-icons@^4.4.0:
   version "4.4.0"
   resolved "https://registry.yarnpkg.com/react-icons/-/react-icons-4.4.0.tgz#a13a8a20c254854e1ec9aecef28a95cdf24ef703"
@@ -3044,6 +3061,18 @@ socket.io-parser@~4.2.0:
     "@socket.io/component-emitter" "~3.1.0"
     debug "~4.3.1"
 
+socket.io@^4.5.2:
+  version "4.5.2"
+  resolved "https://registry.yarnpkg.com/socket.io/-/socket.io-4.5.2.tgz#1eb25fd380ab3d63470aa8279f8e48d922d443ac"
+  integrity sha512-6fCnk4ARMPZN448+SQcnn1u8OHUC72puJcNtSgg2xS34Cu7br1gQ09YKkO1PFfDn/wyUE9ZgMAwosJed003+NQ==
+  dependencies:
+    accepts "~1.3.4"
+    base64id "~2.0.0"
+    debug "~4.3.2"
+    engine.io "~6.2.0"
+    socket.io-adapter "~2.4.0"
+    socket.io-parser "~4.2.0"
+
 "source-map-js@>=0.6.2 <2.0.0", source-map-js@^1.0.2:
   version "1.0.2"
   resolved "https://registry.yarnpkg.com/source-map-js/-/source-map-js-1.0.2.tgz#adbc361d9c62df380125e7f161f71c826f1e490c"

ldm/dream/generator/base.py

@@ -21,6 +21,8 @@ class Generator():
         self.seed                = None
         self.latent_channels     = model.channels
         self.downsampling_factor = downsampling   # BUG: should come from model or config
+        self.perlin              = 0.0
+        self.threshold           = 0
         self.variation_amount    = 0
         self.with_variations     = []
 

ldm/dream/generator/inpaint.py

@@ -27,7 +27,7 @@ class Inpaint(Img2Img):
         # klms samplers not supported yet, so ignore previous sampler
         if isinstance(sampler,KSampler):
             print(
-                f">> sampler '{sampler.__class__.__name__}' is not yet supported for inpainting, using DDIMSampler instead."
+                f">> Using recommended DDIM sampler for inpainting."
             )
             sampler = DDIMSampler(self.model, device=self.model.device)
         

ldm/dream/generator/txt2img2img.py

@@ -40,7 +40,12 @@ class Txt2Img2Img(Generator):
                 init_width // self.downsampling_factor,
             ]
             
-            x = self.get_noise(init_width, init_height)
+            sampler.make_schedule(
+                    ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False
+            )
+            
+            #x = self.get_noise(init_width, init_height)
+            x = x_T
             
             if self.free_gpu_mem and self.model.model.device != self.model.device:
                 self.model.model.to(self.model.device)
@@ -59,7 +64,7 @@ class Txt2Img2Img(Generator):
             )
             
             print(
-                  f"\n>> Interpolating from {init_width}x{init_height} to {width}x{height}"
+                  f"\n>> Interpolating from {init_width}x{init_height} to {width}x{height} using DDIM sampling"
                  )
             
             # resizing
@@ -70,29 +75,19 @@ class Txt2Img2Img(Generator):
             )
 
             t_enc = int(strength * steps)
-
-            x = None
-
-            # Other samplers not supported yet, so ignore previous sampler
-            if not isinstance(sampler,DDIMSampler):
-                print(
-                    f"\n>> Sampler '{sampler.__class__.__name__}' is not yet supported for img2img. Using DDIM sampler"
-                )
-                img_sampler = DDIMSampler(self.model, device=self.model.device)
-                img_sampler.make_schedule(
+            ddim_sampler = DDIMSampler(self.model, device=self.model.device)
+            ddim_sampler.make_schedule(
                     ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False
-                )
-            else:
-                img_sampler = sampler
-            
-            z_enc = img_sampler.stochastic_encode(
+            )
+
+            z_enc = ddim_sampler.stochastic_encode(
                 samples,
                 torch.tensor([t_enc]).to(self.model.device),
-                noise=x_T
+                noise=self.get_noise(width,height,False)
             )
 
             # decode it
-            samples = img_sampler.decode(
+            samples = ddim_sampler.decode(
                 z_enc,
                 c,
                 t_enc,
@@ -110,17 +105,28 @@ class Txt2Img2Img(Generator):
 
 
     # returns a tensor filled with random numbers from a normal distribution
-    def get_noise(self,width,height):
+    def get_noise(self,width,height,scale = True):
+        # print(f"Get noise: {width}x{height}")
+        if scale:
+            trained_square = 512 * 512
+            actual_square = width * height
+            scale = math.sqrt(trained_square / actual_square)
+            scaled_width = math.ceil(scale * width / 64) * 64
+            scaled_height = math.ceil(scale * height / 64) * 64
+        else:
+            scaled_width = width
+            scaled_height = height
+            
         device      = self.model.device
         if device.type == 'mps':
             return torch.randn([1,
                                 self.latent_channels,
-                                height // self.downsampling_factor,
-                                width  // self.downsampling_factor],
+                                scaled_height // self.downsampling_factor,
+                                scaled_width  // self.downsampling_factor],
                                 device='cpu').to(device)
         else:
             return torch.randn([1,
                                 self.latent_channels,
-                                height // self.downsampling_factor,
-                                width  // self.downsampling_factor],
+                                scaled_height // self.downsampling_factor,
+                                scaled_width  // self.downsampling_factor],
                                 device=device)

ldm/dream/restoration/outpaint.py

@@ -13,8 +13,6 @@ class Outpaint(object):
         seed   = old_opt.seed
         prompt = old_opt.prompt
 
-        print(f'DEBUG: old seed={seed}, old prompt = {prompt}')
-
         def wrapped_callback(img,seed,**kwargs):
             image_callback(img,seed,use_prefix=prefix,**kwargs)
 

ldm/generate.py

@@ -174,7 +174,8 @@ class Generate:
             config                = None,
             gfpgan=None,
             codeformer=None,
-            esrgan=None
+            esrgan=None,
+            free_gpu_mem=False,
     ):
         models              = OmegaConf.load(conf)
         mconfig             = models[model]
@@ -201,6 +202,7 @@ class Generate:
         self.gfpgan = gfpgan
         self.codeformer = codeformer
         self.esrgan = esrgan
+        self.free_gpu_mem = free_gpu_mem
 
         # Note that in previous versions, there was an option to pass the
         # device to Generate(). However the device was then ignored, so
@@ -417,7 +419,8 @@ class Generate:
                 generator = self._make_txt2img()
 
             generator.set_variation(
-                self.seed, variation_amount, with_variations)
+                self.seed, variation_amount, with_variations
+            )
             results = generator.generate(
                 prompt,
                 iterations=iterations,
@@ -626,18 +629,14 @@ class Generate:
             height,
         )
 
+        if image.width < self.width and image.height < self.height:
+            print(f'>> WARNING: img2img and inpainting may produce unexpected results with initial images smaller than {self.width}x{self.height} in both dimensions')
+
         # if image has a transparent area and no mask was provided, then try to generate mask
-        if self._has_transparency(image) and not mask:
-            print(
-                '>> Initial image has transparent areas. Will inpaint in these regions.')
-            if self._check_for_erasure(image):
-                print(
-                    '>> WARNING: Colors underneath the transparent region seem to have been erased.\n',
-                    '>>          Inpainting will be suboptimal. Please preserve the colors when making\n',
-                    '>>          a transparency mask, or provide mask explicitly using --init_mask (-M).'
-                )
+        if self._has_transparency(image):
+            self._transparency_check_and_warning(image, mask)
             # this returns a torch tensor
-            init_mask = self._create_init_mask(image,width,height,fit=fit)
+            init_mask = self._create_init_mask(image, width, height, fit=fit)
             
         if (image.width * image.height) > (self.width * self.height):
             print(">> This input is larger than your defaults. If you run out of memory, please use a smaller image.")
@@ -953,6 +952,17 @@ class Generate:
                         colored += 1
         return colored == 0
 
+    def _transparency_check_and_warning(self,image, mask):
+        if not mask:
+            print(
+                '>> Initial image has transparent areas. Will inpaint in these regions.')
+            if self._check_for_erasure(image):
+                print(
+                    '>> WARNING: Colors underneath the transparent region seem to have been erased.\n',
+                    '>>          Inpainting will be suboptimal. Please preserve the colors when making\n',
+                    '>>          a transparency mask, or provide mask explicitly using --init_mask (-M).'
+                )
+
     def _squeeze_image(self, image):
         x, y, resize_needed = self._resolution_check(image.width, image.height)
         if resize_needed:

ldm/models/diffusion/ksampler.py

@@ -5,6 +5,12 @@ import torch.nn as nn
 from ldm.dream.devices import choose_torch_device
 from ldm.models.diffusion.sampler import Sampler
 from ldm.util import rand_perlin_2d
+from ldm.modules.diffusionmodules.util import (
+    make_ddim_sampling_parameters,
+    make_ddim_timesteps,
+    noise_like,
+    extract_into_tensor,
+)
 
 def cfg_apply_threshold(result, threshold = 0.0, scale = 0.7):
     if threshold <= 0.0:
@@ -51,8 +57,9 @@ class KSampler(Sampler):
             schedule,
             steps=model.num_timesteps,
         )
-        self.ds    = None
-        self.s_in  = None
+        self.sigmas = None
+        self.ds     = None
+        self.s_in   = None
 
         def forward(self, x, sigma, uncond, cond, cond_scale):
             x_in = torch.cat([x] * 2)
@@ -81,13 +88,53 @@ class KSampler(Sampler):
         )
         self.model          = outer_model
         self.ddim_num_steps = ddim_num_steps
-        sigmas = self.model.get_sigmas(ddim_num_steps)
-        self.sigmas = sigmas
+        # we don't need both of these sigmas, but storing them here to make
+        # comparison easier later on
+        self.model_sigmas  = self.model.get_sigmas(ddim_num_steps)
+        self.karras_sigmas = K.sampling.get_sigmas_karras(
+            n=ddim_num_steps,
+            sigma_min=self.model.sigmas[0].item(),
+            sigma_max=self.model.sigmas[-1].item(),
+            rho=7.,
+            device=self.device,
+        )
         
     # ALERT: We are completely overriding the sample() method in the base class, which
-    # means that inpainting will (probably?) not work correctly. To get this to work
-    # we need to be able to modify the inner loop of k_heun, k_lms, etc, as is done
-    # in an ugly way in the lstein/k-diffusion branch.
+    # means that inpainting will not work. To get this to work we need to be able to
+    # modify the inner loop of k_heun, k_lms, etc, as is done in an ugly way
+    # in the lstein/k-diffusion branch.
+    
+    @torch.no_grad()
+    def decode(
+            self,
+            z_enc,
+            cond,
+            t_enc,
+            img_callback=None,
+            unconditional_guidance_scale=1.0,
+            unconditional_conditioning=None,
+            use_original_steps=False,
+            init_latent       = None,
+            mask              = None,
+    ):
+        samples,_ = self.sample(
+            batch_size = 1,
+            S          = t_enc,
+            x_T        = z_enc,
+            shape      = z_enc.shape[1:],
+            conditioning = cond,
+            unconditional_guidance_scale=unconditional_guidance_scale,
+            unconditional_conditioning = unconditional_conditioning,
+            img_callback = img_callback,
+            x0           = init_latent,
+            mask         = mask
+            )
+        return samples
+
+    # this is a no-op, provided here for compatibility with ddim and plms samplers
+    @torch.no_grad()
+    def stochastic_encode(self, x0, t, use_original_steps=False, noise=None):
+        return x0
     
     # Most of these arguments are ignored and are only present for compatibility with
     # other samples
@@ -123,24 +170,22 @@ class KSampler(Sampler):
             if img_callback is not None:
                 img_callback(k_callback_values['x'],k_callback_values['i'])
 
-        # sigmas = self.model.get_sigmas(S)
-        # sigmas are now set up in make_schedule - we take the last steps items
-        sigmas = self.sigmas[-S-1:]
-
+        # sigmas are set up in make_schedule - we take the last steps items
+        total_steps = len(self.karras_sigmas)
+        sigmas = self.karras_sigmas[-S-1:]
+        
         if x_T is not None:
-            x = x_T * sigmas[0]
+            x = x_T + torch.randn([batch_size, *shape], device=self.device) * sigmas[0]
         else:
-            x = (
-                torch.randn([batch_size, *shape], device=self.device)
-                * sigmas[0]
-            )   # for GPU draw
+            x = torch.randn([batch_size, *shape], device=self.device) * sigmas[0]
+
         model_wrap_cfg = CFGDenoiser(self.model, threshold=threshold, warmup=max(0.8*S,S-10))
         extra_args = {
             'cond': conditioning,
             'uncond': unconditional_conditioning,
             'cond_scale': unconditional_guidance_scale,
         }
-        print(f'>> Sampling with k_{self.schedule}')
+        print(f'>> Sampling with k_{self.schedule} starting at step {len(self.sigmas)-S-1} of {len(self.sigmas)-1} ({S} new sampling steps)')
         return (
             K.sampling.__dict__[f'sample_{self.schedule}'](
                 model_wrap_cfg, x, sigmas, extra_args=extra_args,
@@ -149,6 +194,8 @@ class KSampler(Sampler):
             None,
         )
 
+    # this code will support inpainting if and when ksampler API modified or
+    # a workaround is found.
     @torch.no_grad()
     def p_sample(
             self,
@@ -196,10 +243,12 @@ class KSampler(Sampler):
         return img, None, None
 
     def get_initial_image(self,x_T,shape,steps):
+        print(f'WARNING: ksampler.get_initial_image(): get_initial_image needs testing')
+        x = (torch.randn(shape, device=self.device) * self.sigmas[0])
         if x_T is not None:
             return x_T + x_T * self.sigmas[0]
         else:
-            return (torch.randn(shape, device=self.device) * self.sigmas[0])
+            return x
         
     def prepare_to_sample(self,t_enc):
         self.t_enc      = t_enc
@@ -213,29 +262,3 @@ class KSampler(Sampler):
         '''
         return self.model.inner_model.q_sample(x0,ts)
 
-    @torch.no_grad()
-    def decode(
-            self,
-            z_enc,
-            cond,
-            t_enc,
-            img_callback=None,
-            unconditional_guidance_scale=1.0,
-            unconditional_conditioning=None,
-            use_original_steps=False,
-            init_latent       = None,
-            mask              = None,
-    ):
-        samples,_ = self.sample(
-            batch_size = 1,
-            S          = t_enc,
-            x_T        = z_enc,
-            shape      = z_enc.shape[1:],
-            conditioning = cond,
-            unconditional_guidance_scale=unconditional_guidance_scale,
-            unconditional_conditioning = unconditional_conditioning,
-            img_callback = img_callback,
-            x0           = init_latent,
-            mask         = mask
-            )
-        return samples

ldm/models/diffusion/sampler.py

@@ -39,6 +39,7 @@ class Sampler(object):
             ddim_eta=0.0,
             verbose=False,
     ):
+        self.total_steps = ddim_num_steps
         self.ddim_timesteps = make_ddim_timesteps(
             ddim_discr_method=ddim_discretize,
             num_ddim_timesteps=ddim_num_steps,
@@ -211,6 +212,7 @@ class Sampler(object):
             if ddim_use_original_steps
             else np.flip(timesteps)
         )
+
         total_steps=steps
 
         iterator = tqdm(
@@ -305,7 +307,7 @@ class Sampler(object):
 
         time_range = np.flip(timesteps)
         total_steps = timesteps.shape[0]
-        print(f'>> Running {self.__class__.__name__} Sampling with {total_steps} timesteps')
+        print(f'>> Running {self.__class__.__name__} sampling starting at step {self.total_steps - t_start} of {self.total_steps} ({total_steps} new sampling steps)')
 
         iterator = tqdm(time_range, desc='Decoding image', total=total_steps)
         x_dec    = x_latent

scripts/dream.py

@@ -75,7 +75,8 @@ def main():
             precision      = opt.precision,
             gfpgan=gfpgan,
             codeformer=codeformer,
-            esrgan=esrgan
+            esrgan=esrgan,
+            free_gpu_mem=opt.free_gpu_mem,
             )
     except (FileNotFoundError, IOError, KeyError) as e:
         print(f'{e}. Aborting.')
@@ -104,8 +105,6 @@ def main():
 
     # preload the model
     gen.load_model()
-    #set additional option
-    gen.free_gpu_mem = opt.free_gpu_mem
 
     # web server loops forever
     if opt.web or opt.gui: