panzoom

CHANGELOG.md

@@ -7,6 +7,7 @@
   - extra networks: add add/remove tags to prompt (e.g. lora activation keywords)
   - extensions: fix couple of compatibility items
   - firefox compatibility improvements
+  - minor image viewer improvements
 - original
   - fix hires secondary sampler  
     this now fully obsoletes `fallback_sampler` and `force_latent_sampler`  

javascript/imageViewer.js

@@ -1,6 +1,7 @@
 // A full size 'lightbox' preview modal shown when left clicking on gallery previews
 let previewDrag = false;
 let modalPreviewZone;
+let previewInstance;
 
 function closeModal(evt, force = false) {
   if (force) gradioApp().getElementById('lightboxModal').style.display = 'none';
@@ -58,7 +59,11 @@ function showModal(event) {
   const source = event.target || event.srcElement;
   const modalImage = gradioApp().getElementById('modalImage');
   const lb = gradioApp().getElementById('lightboxModal');
-  modalImage.onload = () => modalPreviewZone.focus();
+  lb.ownerSVGElement = modalImage;
+  modalImage.onload = () => {
+    previewInstance.moveTo(0, 0);
+    modalPreviewZone.focus();
+  };
   modalImage.src = source.src;
   if (modalImage.style.display === 'none') lb.style.setProperty('background-image', `url(${source.src})`);
   lb.style.display = 'flex';
@@ -111,6 +116,12 @@ function modalTileToggle(event) {
   event.stopPropagation();
 }
 
+function modalResetInstance(event) {
+  const modalImage = document.getElementById('modalImage');
+  previewInstance.dispose();
+  previewInstance = panzoom(modalImage, { zoomSpeed: 0.05, minZoom: 0.1, maxZoom: 5.0, filterKey: (/* e, dx, dy, dz */) => true });
+}
+
 let imageViewerInitialized = false;
 
 function galleryClickEventHandler(event) {
@@ -141,16 +152,14 @@ function initImageViewer() {
   // main elements
   const modal = document.createElement('div');
   modal.id = 'lightboxModal';
-  // modal.addEventListener('keydown', modalKeyHandler, true);
 
   modalPreviewZone = document.createElement('div');
   modalPreviewZone.className = 'lightboxModalPreviewZone';
 
   const modalImage = document.createElement('img');
   modalImage.id = 'modalImage';
-  // modalImage.addEventListener('keydown', modalKeyHandler, true);
   modalPreviewZone.appendChild(modalImage);
-  panzoom(modalImage, { zoomSpeed: 0.05, minZoom: 0.1, maxZoom: 5.0, filterKey: (/* e, dx, dy, dz */) => true });
+  previewInstance = panzoom(modalImage, { zoomSpeed: 0.05, minZoom: 0.1, maxZoom: 5.0, filterKey: (/* e, dx, dy, dz */) => true });
 
   // toolbar
   const modalZoom = document.createElement('span');
@@ -160,6 +169,13 @@ function initImageViewer() {
   modalZoom.title = 'Toggle zoomed view';
   modalZoom.addEventListener('click', modalZoomToggle, true);
 
+  const modalReset = document.createElement('span');
+  modalReset.id = 'modal_reset';
+  modalReset.className = 'cursor';
+  modalReset.innerHTML = '♻️';
+  modalReset.title = 'Reset zoomed view';
+  modalReset.addEventListener('click', modalResetInstance, true);
+
   const modalTile = document.createElement('span');
   modalTile.id = 'modal_tile';
   modalTile.className = 'cursor';
@@ -218,6 +234,7 @@ function initImageViewer() {
   modal.appendChild(modalNext);
   modal.append(modalControls);
   modalControls.appendChild(modalZoom);
+  modalControls.appendChild(modalReset);
   modalControls.appendChild(modalTile);
   modalControls.appendChild(modalSave);
   modalControls.appendChild(modalDownload);

modules/processing_diffusers.py

@@ -18,7 +18,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         shared.state.current_latent = latents
 
     def vae_decode(latents, model, output_type='np'):
-        if hasattr(model, 'vae'):
+        if hasattr(model, 'vae' and isinstance(latents, torch.Tensor)):
             shared.log.debug(f'Diffusers VAE decode: name={model.vae.config.get("_name_or_path", "default")} upcast={model.vae.config.get("force_upcast", None)}')
             decoded = model.vae.decode(latents / model.vae.config.scaling_factor, return_dict=False)[0]
             imgs = model.image_processor.postprocess(decoded, output_type=output_type)
@@ -95,7 +95,12 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
     # from modules.prompt_parser import parse_prompt_attention
     # parsed_prompt = [parse_prompt_attention(prompt) for prompt in prompts]
 
-    shared.sd_model.to(devices.device)
+    if shared.state.interrupted or shared.state.skipped:
+        return results
+
+    if shared.opts.diffusers_move_base:
+        shared.sd_model.to(devices.device)
+
     pipe_args = set_pipeline_args(
         model=shared.sd_model,
         prompt=prompts,
@@ -128,8 +133,9 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
                     images.save_image(decoded[i], path=p.outpath_samples, basename="", seed=seeds[i], prompt=prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-refiner")
 
         if shared.opts.diffusers_move_base:
-            shared.log.debug('Moving base model to CPU')
+            shared.log.debug('Diffusers: Moving base model to CPU')
             shared.sd_model.to('cpu')
+            devices.torch_gc()
 
         if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler) and (p.sampler_name != 'Default'):
             sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
@@ -140,8 +146,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
         if shared.state.interrupted or shared.state.skipped:
             return results
 
-        shared.sd_refiner.to(devices.device)
-        devices.torch_gc()
+        if shared.opts.diffusers_move_refiner:
+            shared.sd_refiner.to(devices.device)
 
         for i in range(len(output.images)):
             pipe_args = set_pipeline_args(
@@ -157,17 +163,15 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
                 denoising_start=p.refiner_denoise_start,
                 denoising_end=p.refiner_denoise_end,
                 image=output.images[i],
-                output_type='latent' if hasattr(shared.sd_model, 'vae') else 'np',
+                output_type='latent' if hasattr(shared.sd_refiner, 'vae') else 'np',
             )
             output = shared.sd_refiner(**pipe_args) # pylint: disable=not-callable
-            if shared.state.interrupted or shared.state.skipped:
-                return results
-
-            output.images = vae_decode(output.images, shared.sd_model)
-            results.append(output.images[0])
+            if not shared.state.interrupted and not shared.state.skipped:
+                output.images = vae_decode(output.images, shared.sd_refiner)
+                results.append(output.images[i])
 
         if shared.opts.diffusers_move_refiner:
-            shared.log.debug('Moving refiner model to CPU')
+            shared.log.debug('Diffusers: Moving refiner model to CPU')
             shared.sd_refiner.to('cpu')
     else:
         results = output.images