clean up result and metadata handling

api/onnx_web/chain/blend_denoise_fastnlmeans.py

@@ -32,9 +32,9 @@ class BlendDenoiseFastNLMeansStage(BaseStage):
         logger.info("denoising source images")
 
         results = []
-        for source in sources.as_numpy():
+        for source in sources.as_arrays():
             data = cv2.cvtColor(source, cv2.COLOR_RGB2BGR)
             data = cv2.fastNlMeansDenoisingColored(data, None, strength, strength)
             results.append(cv2.cvtColor(data, cv2.COLOR_BGR2RGB))
 
-        return StageResult(arrays=results)
+        return StageResult.from_arrays(results, metadata=sources.metadata)

api/onnx_web/chain/blend_denoise_localstd.py

@@ -14,6 +14,11 @@ logger = getLogger(__name__)
 
 
 class BlendDenoiseLocalStdStage(BaseStage):
+    """
+    Experimental stage to blend and denoise images using local means compared to local standard deviation.
+    Very slow.
+    """
+
     max_tile = SizeChart.max
 
     def run(
@@ -35,8 +40,9 @@ class BlendDenoiseLocalStdStage(BaseStage):
         return StageResult.from_arrays(
             [
                 remove_noise(source, threshold=strength, deviation=range)[0]
-                for source in sources.as_numpy()
+                for source in sources.as_arrays()
-            ]
+            ],
+            metadata=sources.metadata,
         )
 
 

api/onnx_web/chain/blend_grid.py

@@ -35,7 +35,7 @@ class BlendGridStage(BaseStage):
     ) -> StageResult:
         logger.info("combining source images using grid layout")
 
-        images = sources.as_image()
+        images = sources.as_images()
         ref_image = images[0]
         size = Size(*ref_image.size)
 
@@ -52,7 +52,9 @@ class BlendGridStage(BaseStage):
             n = order[i]
             output.paste(images[n], (x * size.width, y * size.height))
 
-        return StageResult(images=[*images, output])
+        result = StageResult(source=sources)
+        result.push_image(output, sources.metadata[0])
+        return result
 
     def outputs(
         self,

api/onnx_web/chain/blend_img2img.py

@@ -66,7 +66,7 @@ class BlendImg2ImgStage(BaseStage):
             pipe_params["strength"] = strength
 
         outputs = []
-        for source in sources.as_image():
+        for source in sources.as_images():
             if params.is_lpw():
                 logger.debug("using LPW pipeline for img2img")
                 rng = torch.manual_seed(params.seed)

api/onnx_web/chain/blend_linear.py

@@ -28,9 +28,10 @@ class BlendLinearStage(BaseStage):
     ) -> StageResult:
         logger.info("blending source images using linear interpolation")
 
-        return StageResult(
+        return StageResult.from_images(
-            images=[
+            [
                 Image.blend(source, stage_source, alpha)
-                for source in sources.as_image()
+                for source in sources.as_images()
-            ]
+            ],
+            metadata=sources.metadata,
         )

api/onnx_web/chain/blend_mask.py

@@ -48,6 +48,7 @@ class BlendMaskStage(BaseStage):
         return StageResult.from_images(
             [
                 Image.composite(stage_source_tile, source, mult_mask)
-                for source in sources.as_image()
+                for source in sources.as_images()
-            ]
+            ],
+            metadata=sources.metadata,
         )

api/onnx_web/chain/correct_codeformer.py

@@ -67,7 +67,7 @@ class CorrectCodeformerStage(BaseStage):
         )
 
         results = []
-        for img in sources.as_numpy():
+        for img in sources.as_arrays():
             img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
             # clean all the intermediate results to process the next image
             face_helper.clean_all()
@@ -121,4 +121,4 @@ class CorrectCodeformerStage(BaseStage):
             )
             results.append(Image.fromarray(cv2.cvtColor(output, cv2.COLOR_BGR2RGB)))
 
-        return StageResult.from_images(results)
+        return StageResult.from_images(results, metadata=sources.metadata)

api/onnx_web/chain/correct_gfpgan.py

@@ -74,7 +74,7 @@ class CorrectGFPGANStage(BaseStage):
         gfpgan = self.load(server, stage, upscale, device)
 
         outputs = []
-        for source in sources.as_numpy():
+        for source in sources.as_arrays():
             cropped, restored, result = gfpgan.enhance(
                 source,
                 has_aligned=False,
@@ -84,4 +84,4 @@ class CorrectGFPGANStage(BaseStage):
             )
             outputs.append(result)
 
-        return StageResult.from_arrays(outputs)
+        return StageResult.from_arrays(outputs, metadata=sources.metadata)

api/onnx_web/chain/persist_disk.py

@@ -31,18 +31,14 @@ class PersistDiskStage(BaseStage):
     ) -> StageResult:
         logger.info("persisting %s images to disk: %s", len(sources), output)
 
-        for name, source, metadata in zip(output, sources.as_image(), sources.metadata):
+        for name, source, metadata in zip(
+            output, sources.as_images(), sources.metadata
+        ):
             dest = save_image(
                 server,
                 name,
                 source,
-                params=metadata.params,
+                metadata=metadata,
-                size=metadata.size,
-                upscale=metadata.upscale,
-                border=metadata.border,
-                highres=metadata.highres,
-                inversions=metadata.inversions,
-                loras=metadata.loras,
             )
             logger.info("saved image to %s", dest)
 

api/onnx_web/chain/persist_s3.py

@@ -33,7 +33,8 @@ class PersistS3Stage(BaseStage):
         session = Session(profile_name=profile_name)
         s3 = session.client("s3", endpoint_url=endpoint_url)
 
-        for source, name in zip(sources.as_image(), output):
+        # TODO: save metadata as well
+        for source, name in zip(sources.as_images(), output):
             data = BytesIO()
             source.save(data, format=server.image_format)
             data.seek(0)

api/onnx_web/chain/pipeline.py

@@ -11,7 +11,6 @@ from ..params import ImageParams, Size, StageParams
 from ..server import ServerContext
 from ..utils import is_debug, run_gc
 from ..worker import ProgressCallback, WorkerContext
-from ..worker.command import Progress
 from .base import BaseStage
 from .result import StageResult
 from .tile import needs_tile, process_tile_order
@@ -107,7 +106,7 @@ class ChainPipeline:
         result = self(
             worker, server, params, sources=sources, callback=callback, **kwargs
         )
-        return result.as_image()
+        return result.as_images()
 
     def stage(self, callback: BaseStage, params: StageParams, **kwargs):
         self.stages.append((callback, params, kwargs))
@@ -184,7 +183,7 @@ class ChainPipeline:
                         size=kwargs.get("size", None),
                         source=source,
                     )
-                    for source in stage_sources.as_image()
+                    for source in stage_sources.as_images()
                 ]
             )
 
@@ -302,7 +301,7 @@ class ChainPipeline:
             )
 
             if is_debug():
-                for j, image in enumerate(stage_sources.as_image()):
+                for j, image in enumerate(stage_sources.as_images()):
                     save_image(server, f"last-stage-{j}.png", image)
 
         end = monotonic()

api/onnx_web/chain/reduce_crop.py

@@ -28,11 +28,11 @@ class ReduceCropStage(BaseStage):
     ) -> StageResult:
         outputs = []
 
-        for source in sources.as_image():
+        for source in sources.as_images():
             image = source.crop((origin.width, origin.height, size.width, size.height))
             logger.info(
                 "created thumbnail with dimensions: %sx%s", image.width, image.height
             )
             outputs.append(image)
 
-        return StageResult(images=outputs)
+        return StageResult.from_images(outputs, metadata=sources.metadata)

api/onnx_web/chain/reduce_thumbnail.py

@@ -26,7 +26,7 @@ class ReduceThumbnailStage(BaseStage):
     ) -> StageResult:
         outputs = []
 
-        for source in sources.as_image():
+        for source in sources.as_images():
             image = source.copy()
 
             image = image.thumbnail((size.width, size.height))
@@ -37,4 +37,4 @@ class ReduceThumbnailStage(BaseStage):
 
             outputs.append(image)
 
-        return StageResult(images=outputs)
+        return StageResult.from_images(outputs, metadata=sources.metadata)

api/onnx_web/chain/result.py

@@ -194,12 +194,16 @@ class StageResult:
         return StageResult(images=[])
 
     @staticmethod
-    def from_arrays(arrays: List[np.ndarray]):
+    def from_arrays(
-        return StageResult(arrays=arrays)
+        arrays: List[np.ndarray], metadata: Optional[List[ImageMetadata]] = None
+    ):
+        return StageResult(arrays=arrays, metadata=metadata)
 
     @staticmethod
-    def from_images(images: List[Image.Image]):
+    def from_images(
-        return StageResult(images=images)
+        images: List[Image.Image], metadata: Optional[List[ImageMetadata]] = None
+    ):
+        return StageResult(images=images, metadata=metadata)
 
     def __init__(
         self,
@@ -208,14 +212,21 @@ class StageResult:
         metadata: Optional[List[ImageMetadata]] = None,
         source: Optional[Any] = None,
     ) -> None:
-        if sum([arrays is not None, images is not None, source is not None]) > 1:
+        data_provided = sum(
-            raise ValueError("stages must only return one type of result")
+            [arrays is not None, images is not None, source is not None]
-        elif arrays is None and images is None and source is None:
+        )
-            raise ValueError("stages must return results")
+        if data_provided > 1:
+            raise ValueError("results must only contain one type of data")
+        elif data_provided == 0:
+            raise ValueError("results must contain some data")
 
+        if source is not None:
+            self.arrays = source.arrays
+            self.images = source.images
+            self.metadata = source.metadata
+        else:
             self.arrays = arrays
             self.images = images
-        self.source = source
             self.metadata = metadata or []
 
     def __len__(self) -> int:
@@ -226,7 +237,7 @@ class StageResult:
         else:
             return 0
 
-    def as_numpy(self) -> List[np.ndarray]:
+    def as_arrays(self) -> List[np.ndarray]:
         if self.arrays is not None:
             return self.arrays
         elif self.images is not None:
@@ -234,7 +245,7 @@ class StageResult:
         else:
             return []
 
-    def as_image(self) -> List[Image.Image]:
+    def as_images(self) -> List[Image.Image]:
         if self.images is not None:
             return self.images
         elif self.arrays is not None:
@@ -242,7 +253,7 @@ class StageResult:
         else:
             return []
 
-    def push_array(self, array: np.ndarray, metadata: Optional[ImageMetadata]):
+    def push_array(self, array: np.ndarray, metadata: ImageMetadata):
         if self.arrays is not None:
             self.arrays.append(array)
         elif self.images is not None:
@@ -253,9 +264,9 @@ class StageResult:
         if metadata is not None:
             self.metadata.append(metadata)
         else:
-            self.metadata.append(ImageMetadata())
+            raise ValueError("metadata must be provided")
 
-    def push_image(self, image: Image.Image, metadata: Optional[ImageMetadata]):
+    def push_image(self, image: Image.Image, metadata: ImageMetadata):
         if self.images is not None:
             self.images.append(image)
         elif self.arrays is not None:
@@ -266,11 +277,9 @@ class StageResult:
         if metadata is not None:
             self.metadata.append(metadata)
         else:
-            self.metadata.append(ImageMetadata())
+            raise ValueError("metadata must be provided")
 
-    def insert_array(
+    def insert_array(self, index: int, array: np.ndarray, metadata: ImageMetadata):
-        self, index: int, array: np.ndarray, metadata: Optional[ImageMetadata]
-    ):
         if self.arrays is not None:
             self.arrays.insert(index, array)
         elif self.images is not None:
@@ -283,11 +292,9 @@ class StageResult:
         if metadata is not None:
             self.metadata.insert(index, metadata)
         else:
-            self.metadata.insert(index, ImageMetadata())
+            raise ValueError("metadata must be provided")
 
-    def insert_image(
+    def insert_image(self, index: int, image: Image.Image, metadata: ImageMetadata):
-        self, index: int, image: Image.Image, metadata: Optional[ImageMetadata]
-    ):
         if self.images is not None:
             self.images.insert(index, image)
         elif self.arrays is not None:
@@ -298,7 +305,28 @@ class StageResult:
         if metadata is not None:
             self.metadata.insert(index, metadata)
         else:
-            self.metadata.insert(index, ImageMetadata())
+            raise ValueError("metadata must be provided")
+
+    def size(self) -> Size:
+        if self.images is not None:
+            return Size(self.images[0].width, self.images[0].height)
+        elif self.arrays is not None:
+            return Size(
+                self.arrays[0].shape[0], self.arrays[0].shape[1]
+            )  # TODO: which fields within the shape are width/height?
+        else:
+            return Size(0, 0)
+
+    def validate(self) -> None:
+        """
+        Make sure the data exists and that data and metadata match in length.
+        """
+
+        if self.arrays is None and self.images is None:
+            raise ValueError("no data in result")
+
+        if len(self) != len(self.metadata):
+            raise ValueError("metadata and data do not match in length")
 
 
 def shape_mode(arr: np.ndarray) -> str:

api/onnx_web/chain/source_noise.py

@@ -36,13 +36,13 @@ class SourceNoiseStage(BaseStage):
         outputs = []
 
         # TODO: looping over sources and ignoring params does not make much sense for a source stage
-        for source in sources.as_image():
+        for source in sources.as_images():
             output = noise_source(source, (size.width, size.height), (0, 0))
 
             logger.info("final output image size: %sx%s", output.width, output.height)
             outputs.append(output)
 
-        return StageResult(images=outputs)
+        return StageResult.from_images(outputs, metadata=sources.metadata)
 
     def outputs(
         self,

api/onnx_web/chain/source_s3.py

@@ -37,7 +37,7 @@ class SourceS3Stage(BaseStage):
                 "source images were passed to a source stage, new images will be appended"
             )
 
-        outputs = sources.as_image()
+        outputs = sources.as_images()
         for key in source_keys:
             try:
                 logger.info("loading image from s3://%s/%s", bucket, key)

api/onnx_web/chain/source_url.py

@@ -34,7 +34,7 @@ class SourceURLStage(BaseStage):
                 "source images were passed to a source stage, new images will be appended"
             )
 
-        outputs = sources.as_image()
+        outputs = sources.as_images()
         for url in source_urls:
             response = requests.get(url)
             output = Image.open(BytesIO(response.content))

api/onnx_web/chain/tile.py

@@ -257,7 +257,7 @@ def process_tile_stack(
     overlap: float = 0.5,
     **kwargs,
 ) -> List[Image.Image]:
-    sources = stack.as_image()
+    sources = stack.as_images()
 
     width, height = kwargs.get("size", sources[0].size if len(sources) > 0 else None)
     mask = kwargs.get("mask", kwargs.get("stage_mask", None))
@@ -308,7 +308,7 @@ def process_tile_stack(
                 bottom_margin,
             )
             tile_stack = add_margin(
-                stack.as_image(),
+                stack.as_images(),
                 left,
                 top,
                 right,
@@ -346,7 +346,7 @@ def process_tile_stack(
         if isinstance(tile_stack, list):
             tile_stack = StageResult.from_images(tile_stack)
 
-        tiles.append((left, top, tile_stack.as_image()))
+        tiles.append((left, top, tile_stack.as_images()))
 
     lefts, tops, stacks = list(zip(*tiles))
     coords = list(zip(lefts, tops))
@@ -516,7 +516,7 @@ def get_result_tile(
     top, left = origin
     return [
         layer.crop((top, left, top + tile.height, left + tile.width))
-        for layer in result.as_image()
+        for layer in result.as_images()
     ]
 
 

api/onnx_web/chain/upscale_bsrgan.py

@@ -79,7 +79,7 @@ class UpscaleBSRGANStage(BaseStage):
         bsrgan = self.load(server, stage, upscale, device)
 
         outputs = []
-        for source in sources.as_numpy():
+        for source in sources.as_arrays():
             image = source / 255.0
             image = image[:, :, [2, 1, 0]].astype(np.float32).transpose((2, 0, 1))
             image = np.expand_dims(image, axis=0)
@@ -105,7 +105,7 @@ class UpscaleBSRGANStage(BaseStage):
             logger.debug("output image shape: %s", output.shape)
             outputs.append(output)
 
-        return StageResult(arrays=outputs)
+        return StageResult(arrays=outputs, metadata=sources.metadata)
 
     def steps(
         self,

api/onnx_web/chain/upscale_highres.py

@@ -42,7 +42,7 @@ class UpscaleHighresStage(BaseStage):
                 source,
                 callback=callback,
             )
-            for source in sources.as_image()
+            for source in sources.as_images()
         ]
 
-        return StageResult(images=outputs)
+        return StageResult(images=outputs, metadata=sources.metadata)

api/onnx_web/chain/upscale_outpaint.py

@@ -62,7 +62,7 @@ class UpscaleOutpaintStage(BaseStage):
         )
 
         outputs = []
-        for source in sources.as_image():
+        for source in sources.as_images():
             if is_debug():
                 save_image(server, "tile-source.png", source)
                 save_image(server, "tile-mask.png", tile_mask)
@@ -123,4 +123,4 @@ class UpscaleOutpaintStage(BaseStage):
 
             outputs.extend(result.images)
 
-        return StageResult(images=outputs)
+        return StageResult(images=outputs, metadata=sources.metadata)

api/onnx_web/chain/upscale_resrgan.py

@@ -112,7 +112,7 @@ class UpscaleRealESRGANStage(BaseStage):
         )
 
         outputs = []
-        for source in sources.as_numpy():
+        for source in sources.as_arrays():
             output, _ = upsampler.enhance(source, outscale=upscale.outscale)
             logger.info("final output image size: %s", output.shape)
             outputs.append(output)

api/onnx_web/chain/upscale_simple.py

@@ -33,7 +33,7 @@ class UpscaleSimpleStage(BaseStage):
             return sources
 
         outputs = []
-        for source in sources.as_image():
+        for source in sources.as_images():
             scaled_size = (source.width * upscale.scale, source.height * upscale.scale)
 
             if method == "bilinear":
@@ -49,4 +49,4 @@ class UpscaleSimpleStage(BaseStage):
             else:
                 logger.warning("unknown upscaling method: %s", method)
 
-        return StageResult(images=outputs)
+        return StageResult(images=outputs, metadata=sources.metadata)

api/onnx_web/chain/upscale_stable_diffusion.py

@@ -59,7 +59,7 @@ class UpscaleStableDiffusionStage(BaseStage):
             pipeline.unet.set_prompts(prompt_embeds)
 
         outputs = []
-        for source in sources.as_image():
+        for source in sources.as_images():
             result = pipeline(
                 prompt,
                 source,
@@ -73,4 +73,4 @@ class UpscaleStableDiffusionStage(BaseStage):
             )
             outputs.extend(result.images)
 
-        return StageResult(images=outputs)
+        return StageResult(images=outputs, metadata=sources.metadata)

api/onnx_web/chain/upscale_swinir.py

@@ -72,7 +72,7 @@ class UpscaleSwinIRStage(BaseStage):
         swinir = self.load(server, stage, upscale, device)
 
         outputs = []
-        for source in sources.as_numpy():
+        for source in sources.as_arrays():
             # TODO: add support for grayscale (1-channel) images
             image = source / 255.0
             image = image[:, :, [2, 1, 0]].astype(np.float32).transpose((2, 0, 1))
@@ -98,4 +98,4 @@ class UpscaleSwinIRStage(BaseStage):
             logger.info("output image size: %s", output.shape)
             outputs.append(output)
 
-        return StageResult(images=outputs)
+        return StageResult(images=outputs, metadata=sources.metadata)

api/onnx_web/diffusers/run.py

@@ -118,7 +118,7 @@ def run_txt2img_pipeline(
     )
 
     # add a thumbnail, if requested
-    cover = images.as_image()[0]
+    cover = images.as_images()[0]
     if params.thumbnail and (
         cover.width > server.thumbnail_size or cover.height > server.thumbnail_size
     ):
@@ -385,12 +385,12 @@ def run_inpaint_pipeline(
         worker,
         server,
         params,
-        StageResult(images=[source]),
+        StageResult(images=[source]),  # TODO: load metadata from source image
         callback=progress,
         latents=latents,
     )
 
-    for i, image, metadata in enumerate(zip(images.as_image(), images.metadata)):
+    for i, image, metadata in enumerate(zip(images.as_images(), images.metadata)):
         if full_res_inpaint:
             if is_debug():
                 save_image(server, "adjusted-output.png", image)

api/onnx_web/output.py

@@ -62,7 +62,7 @@ def save_result(
     result: StageResult,
     base_name: str,
 ) -> List[str]:
-    images = result.as_image()
+    images = result.as_images()
     outputs = make_output_names(server, base_name, len(images))
     results = []
     for image, metadata, filename in zip(images, result.metadata, outputs):