WAS_Image_Style_Filter: Allow batch processing
This commit is contained in:
Jordan Thompson
+50
-52
@@ -2738,7 +2738,7 @@ class WAS_Image_Filters:
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del blend_mask, edge_enhanced_img
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# Output image
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out_image = (pil2tensor(pil_image) if pil_image else image)
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tensors.appendpil2tensor(pil2tensor(pil_image) if pil_image else image)
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return (out_image, )
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@@ -2803,74 +2803,72 @@ class WAS_Image_Style_Filter:
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# Import Pilgram module
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import pilgram
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# Convert image to PIL
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image = tensor2pil(image)
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# WAS Filters
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WTools = WAS_Tools_Class()
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# Apply blending
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if style:
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tensors = []
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for img in images:
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if style == "1977":
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out_image = pilgram._1977(image)
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tensors.append(pil2tensor(pilgram._1977(tensor2pil(img))))
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elif style == "aden":
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out_image = pilgram.aden(image)
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tensors.append(pil2tensor(pilgram.aden(tensor2pil(img))))
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elif style == "brannan":
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out_image = pilgram.brannan(image)
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tensors.append(pil2tensor(pilgram.brannan(tensor2pil(img))))
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elif style == "brooklyn":
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out_image = pilgram.brooklyn(image)
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tensors.append(pil2tensor(pilgram.brooklyn(tensor2pil(img))))
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elif style == "clarendon":
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out_image = pilgram.clarendon(image)
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tensors.append(pil2tensor(pilgram.clarendon(tensor2pil(img))))
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elif style == "earlybird":
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out_image = pilgram.earlybird(image)
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tensors.append(pil2tensor(pilgram.earlybird(tensor2pil(img))))
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elif style == "fairy tale":
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out_image = WTools.sparkle(image)
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tensors.append(pil2tensor(WTools.sparkle(tensor2pil(img))))
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elif style == "gingham":
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out_image = pilgram.gingham(image)
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tensors.append(pil2tensor(pilgram.gingham(tensor2pil(img))))
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elif style == "hudson":
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out_image = pilgram.hudson(image)
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tensors.append(pil2tensor(pilgram.hudson(tensor2pil(img))))
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elif style == "inkwell":
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out_image = pilgram.inkwell(image)
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tensors.append(pil2tensor(pilgram.inkwell(tensor2pil(img))))
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elif style == "kelvin":
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out_image = pilgram.kelvin(image)
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tensors.append(pil2tensor(pilgram.kelvin(tensor2pil(img))))
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elif style == "lark":
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out_image = pilgram.lark(image)
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tensors.append(pil2tensor(pilgram.lark(tensor2pil(img))))
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elif style == "lofi":
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out_image = pilgram.lofi(image)
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tensors.append(pil2tensor(pilgram.lofi(tensor2pil(img))))
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elif style == "maven":
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out_image = pilgram.maven(image)
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tensors.append(pil2tensor(pilgram.maven(tensor2pil(img))))
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elif style == "mayfair":
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out_image = pilgram.mayfair(image)
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tensors.append(pil2tensor(pilgram.mayfair(tensor2pil(img))))
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elif style == "moon":
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out_image = pilgram.moon(image)
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tensors.append(pil2tensor(pilgram.moon(tensor2pil(img))))
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elif style == "nashville":
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out_image = pilgram.nashville(image)
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tensors.append(pil2tensor(pilgram.nashville(tensor2pil(img))))
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elif style == "perpetua":
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out_image = pilgram.perpetua(image)
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tensors.appendpil2tensorpilgram.perpetua(tensor2pil(img))))
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elif style == "reyes":
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out_image = pilgram.reyes(image)
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tensors.appendpil2tensorpilgram.reyes(tensor2pil(img))))
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elif style == "rise":
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out_image = pilgram.rise(image)
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tensors.appendpil2tensorpilgram.rise(tensor2pil(img))))
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elif style == "slumber":
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out_image = pilgram.slumber(image)
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tensors.appendpil2tensorpilgram.slumber(tensor2pil(img))))
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elif style == "stinson":
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out_image = pilgram.stinson(image)
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tensors.appendpil2tensorpilgram.stinson(tensor2pil(img))))
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elif style == "toaster":
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out_image = pilgram.toaster(image)
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tensors.appendpil2tensorpilgram.toaster(tensor2pil(img))))
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elif style == "valencia":
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out_image = pilgram.valencia(image)
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tensors.appendpil2tensorpilgram.valencia(tensor2pil(img))))
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elif style == "walden":
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out_image = pilgram.walden(image)
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tensors.appendpil2tensorpilgram.walden(tensor2pil(img))))
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elif style == "willow":
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out_image = pilgram.willow(image)
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tensors.appendpil2tensorpilgram.willow(tensor2pil(img))))
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elif style == "xpro2":
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out_image = pilgram.xpro2(image)
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tensors.appendpil2tensorpilgram.xpro2(tensor2pil(img))))
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else:
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out_image = image
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tensors.append(img)
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out_image = out_image.convert("RGB")
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tensors = torch.cat(tensors, dim=0)
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return (torch.from_numpy(np.array(out_image).astype(np.float32) / 255.0).unsqueeze(0), )
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return (tensors, )
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# IMAGE CROP FACE
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@@ -3840,43 +3838,43 @@ class WAS_Image_Blending_Mode:
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# Apply blending
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if mode:
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if mode == "color":
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out_image = pilgram.css.blending.color(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.color(img_a, img_b)
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elif mode == "color_burn":
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out_image = pilgram.css.blending.color_burn(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.color_burn(img_a, img_b)
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elif mode == "color_dodge":
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out_image = pilgram.css.blending.color_dodge(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.color_dodge(img_a, img_b)
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elif mode == "darken":
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out_image = pilgram.css.blending.darken(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.darken(img_a, img_b)
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elif mode == "difference":
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out_image = pilgram.css.blending.difference(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.difference(img_a, img_b)
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elif mode == "exclusion":
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out_image = pilgram.css.blending.exclusion(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.exclusion(img_a, img_b)
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elif mode == "hard_light":
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out_image = pilgram.css.blending.hard_light(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.hard_light(img_a, img_b)
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elif mode == "hue":
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out_image = pilgram.css.blending.hue(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.hue(img_a, img_b)
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elif mode == "lighten":
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out_image = pilgram.css.blending.lighten(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.lighten(img_a, img_b)
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elif mode == "multiply":
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out_image = pilgram.css.blending.multiply(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.multiply(img_a, img_b)
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elif mode == "add":
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out_image = pilgram.css.blending.normal(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.normal(img_a, img_b)
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elif mode == "overlay":
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out_image = pilgram.css.blending.overlay(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.overlay(img_a, img_b)
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elif mode == "screen":
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out_image = pilgram.css.blending.screen(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.screen(img_a, img_b)
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elif mode == "soft_light":
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out_image = pilgram.css.blending.soft_light(img_a, img_b)
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tensors.appendpil2tensorpilgram.css.blending.soft_light(img_a, img_b)
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else:
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out_image = img_a
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tensors.appendpil2tensorimg_a
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out_image = out_image.convert("RGB")
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tensors.appendpil2tensorout_image.convert("RGB")
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# Blend image
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blend_mask = Image.new(mode="L", size=img_a.size,
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color=(round(blend_percentage * 255)))
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blend_mask = ImageOps.invert(blend_mask)
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out_image = Image.composite(img_a, out_image, blend_mask)
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tensors.appendpil2tensorImage.composite(img_a, out_image, blend_mask)
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return (pil2tensor(out_image), )
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