fix(api): better handling of alpha channels

api/onnx_web/chain/blend_grid.py

@@ -3,7 +3,7 @@
 
 from PIL import Image
 
-from ..params import ImageParams, SizeChart, StageParams
+from ..params import ImageParams, Size, SizeChart, StageParams
 from ..server import ServerContext
 from ..worker import ProgressCallback, WorkerContext
 from .base import BaseStage
@@ -36,9 +36,10 @@ def run(
         logger.info("combining source images using grid layout")
 
         images = sources.as_image()
-        size = images[0].size
+        ref_image = images[0]
+        size = Size(*ref_image.size)
 
-        output = Image.new("RGB", (size[0] * width, size[1] * height))
+        output = Image.new(ref_image.mode, (size.width * width, size.height * height))
 
         # TODO: labels
         if order is None:
@@ -49,7 +50,7 @@ def run(
             y = i // width
 
             n = order[i]
-            output.paste(images[n], (x * size[0], y * size[1]))
+            output.paste(images[n], (x * size.width, y * size.height))
 
         return StageResult(images=[*images, output])
 

api/onnx_web/chain/blend_mask.py

@@ -30,7 +30,8 @@ def run(
     ) -> StageResult:
         logger.info("blending image using mask")
 
-        mult_mask = Image.new("RGBA", stage_mask.size, color="black")
+        # TODO: does this need an alpha channel?
+        mult_mask = Image.new(stage_mask.mode, stage_mask.size, color="black")
         mult_mask.alpha_composite(stage_mask)
         mult_mask = mult_mask.convert("L")
 

api/onnx_web/chain/result.py

@@ -52,4 +52,16 @@ def as_image(self) -> List[Image.Image]:
         if self.images is not None:
             return self.images
 
-        return [Image.fromarray(np.uint8(i), "RGB") for i in self.arrays]
+        return [Image.fromarray(np.uint8(i), shape_mode(i)) for i in self.arrays]
+
+
+def shape_mode(arr: np.ndarray) -> str:
+    if len(arr.shape) != 3:
+        raise ValueError("unknown array format")
+
+    if arr.shape[-1] == 3:
+        return "RGB"
+    elif arr.shape[-1] == 4:
+        return "RGBA"
+
+    raise ValueError("unknown image format")

api/onnx_web/chain/tile.py

@@ -151,7 +151,9 @@ def blend_tiles(
         "adjusting tile size from %s to %s based on %s overlap", tile, adj_tile, overlap
     )
 
-    scaled_size = (height * scale, width * scale, 3)
+    channels = max([4 if tile_image.mode == "RGBA" else 3 for _left, _top, tile_image in tiles])
+    scaled_size = (height * scale, width * scale, channels)
+
     count = np.zeros(scaled_size)
     value = np.zeros(scaled_size)
 
@@ -221,7 +223,7 @@ def blend_tiles(
                 margin_left : equalized.shape[1] + margin_right,
                 np.newaxis,
             ],
-            3,
+            channels,
             axis=2,
         )
 

api/onnx_web/image/mask_filter.py

@@ -8,7 +8,7 @@ def mask_filter_none(
 ) -> Image.Image:
     width, height = dims
 
-    noise = Image.new("RGB", (width, height), fill)
+    noise = Image.new(mask.mode, (width, height), fill)
     noise.paste(mask, origin)
 
     return noise

api/onnx_web/image/noise_source.py

@@ -17,21 +17,21 @@ def noise_source_fill_edge(
     """
     width, height = dims
 
-    noise = Image.new("RGB", (width, height), fill)
+    noise = Image.new(source.mode, (width, height), fill)
     noise.paste(source, origin)
 
     return noise
 
 
 def noise_source_fill_mask(
-    _source: Image.Image, dims: Point, _origin: Point, fill="white", **kw
+    source: Image.Image, dims: Point, _origin: Point, fill="white", **kw
 ) -> Image.Image:
     """
     Fill the whole canvas, no source or noise.
     """
     width, height = dims
 
-    noise = Image.new("RGB", (width, height), fill)
+    noise = Image.new(source.mode, (width, height), fill)
 
     return noise
 
@@ -52,7 +52,7 @@ def noise_source_gaussian(
 
 
 def noise_source_uniform(
-    _source: Image.Image, dims: Point, _origin: Point, **kw
+    source: Image.Image, dims: Point, _origin: Point, **kw
 ) -> Image.Image:
     width, height = dims
     size = width * height
@@ -61,18 +61,19 @@ def noise_source_uniform(
     noise_g = random.uniform(0, 256, size=size)
     noise_b = random.uniform(0, 256, size=size)
 
+    # needs to be RGB for pixel manipulation
     noise = Image.new("RGB", (width, height))
 
     for x in range(width):
         for y in range(height):
             i = get_pixel_index(x, y, width)
             noise.putpixel((x, y), (int(noise_r[i]), int(noise_g[i]), int(noise_b[i])))
 
-    return noise
+    return noise.convert(source.mode)
 
 
 def noise_source_normal(
-    _source: Image.Image, dims: Point, _origin: Point, **kw
+    source: Image.Image, dims: Point, _origin: Point, **kw
 ) -> Image.Image:
     width, height = dims
     size = width * height
@@ -81,14 +82,15 @@ def noise_source_normal(
     noise_g = random.normal(128, 32, size=size)
     noise_b = random.normal(128, 32, size=size)
 
+    # needs to be RGB for pixel manipulation
     noise = Image.new("RGB", (width, height))
 
     for x in range(width):
         for y in range(height):
             i = get_pixel_index(x, y, width)
             noise.putpixel((x, y), (int(noise_r[i]), int(noise_g[i]), int(noise_b[i])))
 
-    return noise
+    return noise.convert(source.mode)
 
 
 def noise_source_histogram(
@@ -112,11 +114,12 @@ def noise_source_histogram(
         256, p=np.divide(np.copy(hist_b), np.sum(hist_b)), size=size
     )
 
+    # needs to be RGB for pixel manipulation
     noise = Image.new("RGB", (width, height))
 
     for x in range(width):
         for y in range(height):
             i = get_pixel_index(x, y, width)
             noise.putpixel((x, y), (noise_r[i], noise_g[i], noise_b[i]))
 
-    return noise
+    return noise.convert(source.mode)

api/onnx_web/image/utils.py

@@ -20,7 +20,7 @@ def expand_image(
     size = tuple(size)
     origin = (expand.left, expand.top)
 
-    full_source = Image.new("RGB", size, fill)
+    full_source = Image.new(source.mode, size, fill)
     full_source.paste(source, origin)
 
     # new mask pixels need to be filled with white so they will be replaced