v0.30.5
This commit is contained in:
kk8bit
+11
-22
@@ -9,52 +9,47 @@ class ImageComposer:
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"required": {
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"image_a": ("IMAGE",),
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"mask_a": ("MASK",),
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"image_b": ("IMAGE",),
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"image_b": ("IMAGE",),
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"position": (["top", "bottom", "left", "right"], {"default": "top"}),
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},
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"optional": {
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"mask_b": ("MASK",),
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"mask_b": ("MASK",),
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}
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}
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RETURN_TYPES = ("IMAGE", "MASK", "DATA")
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RETURN_NAMES = ("IMAGE", "MASK", "DATA")
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RETURN_TYPES = ("DATA", "IMAGE", "MASK")
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RETURN_NAMES = ("DATA", "IMAGE", "MASK")
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FUNCTION = "compose_images"
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CATEGORY = "KayTool/Image"
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def compose_images(self, image_a, mask_a=None, image_b=None, position=None, mask_b=None):
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image_a = image_a[0].cpu().numpy()
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image_a = image_a[0].cpu().numpy()
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image_a_pil = Image.fromarray((image_a * 255).astype(np.uint8))
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a_width, a_height = image_a_pil.size
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image_b = image_b[0].cpu().numpy()
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image_b_pil = Image.fromarray((image_b * 255).astype(np.uint8))
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b_width, b_height = image_b_pil.size
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if mask_a is None:
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mask_a_np = np.zeros((a_height, a_width), dtype=np.uint8)
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else:
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mask_a_np = (mask_a.cpu().numpy() * 255).astype(np.uint8)
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if mask_a_np.ndim == 3:
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if mask_a_np.ndim == 3:
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mask_a_np = mask_a_np.squeeze()
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mask_a_pil = Image.fromarray(mask_a_np)
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if position in ["top", "bottom"]:
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scale = a_width / b_width
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new_b_width = a_width
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new_b_height = int(b_height * scale)
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else:
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else:
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scale = a_height / b_height
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new_b_width = int(b_width * scale)
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new_b_height = a_height
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image_b_pil = image_b_pil.resize((new_b_width, new_b_height), Image.Resampling.LANCZOS)
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if position in ["top", "bottom"]:
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new_width = a_width
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new_height = a_height + new_b_height
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@@ -62,7 +57,6 @@ class ImageComposer:
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new_width = a_width + new_b_width
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new_height = a_height
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composed_image = Image.new("RGB", (new_width, new_height), (0, 0, 0))
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if position == "top":
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composed_image.paste(image_a_pil, (0, 0))
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@@ -79,22 +73,20 @@ class ImageComposer:
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composed_image.paste(image_b_pil, (a_width, 0))
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a_pos = (0, 0, a_width, a_height)
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b_pos = (a_width, 0, new_width, new_b_height)
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else:
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else:
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composed_image.paste(image_b_pil, (0, 0))
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composed_image.paste(image_a_pil, (new_b_width, 0))
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a_pos = (new_b_width, 0, new_width, a_height)
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b_pos = (0, 0, new_b_width, new_b_height)
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mask_out = Image.new("L", (new_width, new_height), 0)
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mask_out = Image.new("L", (new_width, new_height), 0)
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mask_out.paste(mask_a_pil, (a_pos[0], a_pos[1]))
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if mask_b is None:
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mask_b_np = np.zeros((b_height, b_width), dtype=np.uint8)
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else:
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mask_b_np = (mask_b.cpu().numpy() * 255).astype(np.uint8)
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if mask_b_np.ndim == 3:
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if mask_b_np.ndim == 3:
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mask_b_np = mask_b_np.squeeze()
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mask_b_pil = Image.fromarray(mask_b_np).resize((new_b_width, new_b_height), Image.Resampling.LANCZOS)
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mask_out.paste(mask_b_pil, (b_pos[0], b_pos[1]))
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@@ -102,14 +94,11 @@ class ImageComposer:
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composed_image_tensor = torch.from_numpy(np.array(composed_image).astype(np.float32) / 255.0).unsqueeze(0)
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mask_out_tensor = torch.from_numpy(np.array(mask_out).astype(np.float32) / 255.0)
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data = {
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"a_position": a_pos,
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"b_position": b_pos,
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"a_size": (a_width, a_height),
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"b_size": (new_b_width, new_b_height),
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"composed_image": composed_image_tensor,
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"mask_out": mask_out_tensor,
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}
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return (composed_image_tensor, mask_out_tensor, data)
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return (data, composed_image_tensor, mask_out_tensor)
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+14
-16
@@ -7,8 +7,12 @@ class ImageCropper:
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image_composer_data": ("DATA",),
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"target": (["a", "b"], {"default": "a"}),
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"image_composer_data": ("DATA",),
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"image": ("IMAGE",),
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"target": (["a", "b"], {"default": "a"}),
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},
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"optional": {
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"mask": ("MASK",),
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}
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}
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@@ -17,32 +21,26 @@ class ImageCropper:
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FUNCTION = "crop_image"
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CATEGORY = "KayTool/Image"
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def crop_image(self, image_composer_data, target):
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composed_image_tensor = image_composer_data.get("composed_image")
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mask_out_tensor = image_composer_data.get("mask_out")
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image = composed_image_tensor[0].cpu().numpy()
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def crop_image(self, image_composer_data, image, target, mask=None):
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image = image[0].cpu().numpy()
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image_pil = Image.fromarray((image * 255).astype(np.uint8))
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orig_height, orig_width = image_pil.size[1], image_pil.size[0]
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if target == "a":
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x1, y1, x2, y2 = image_composer_data["a_position"]
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else: # "b"
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else:
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x1, y1, x2, y2 = image_composer_data["b_position"]
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cropped_image = image_pil.crop((x1, y1, x2, y2))
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mask_np = (mask_out_tensor.cpu().numpy() * 255).astype(np.uint8)
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if mask_np.ndim == 3:
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if mask is None:
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mask = torch.zeros((orig_height, orig_width), dtype=torch.float32)
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mask_np = (mask.cpu().numpy() * 255).astype(np.uint8)
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if mask_np.ndim == 3:
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mask_np = mask_np.squeeze()
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mask_pil = Image.fromarray(mask_np)
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cropped_mask = mask_pil.crop((x1, y1, x2, y2))
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cropped_image_tensor = torch.from_numpy(np.array(cropped_image).astype(np.float32) / 255.0).unsqueeze(0)
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cropped_mask_tensor = torch.from_numpy(np.array(cropped_mask).astype(np.float32) / 255.0)
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+1
-1
@@ -1,7 +1,7 @@
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[project]
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name = "kaytool"
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description ="KayTool boosts ComfyUI workflow efficiency with ultra-practical tools: BiRefNet/RemBG for background/mask tasks, wireless data transfer (Get & Out), AI translation (Tencent/Baidu), dynamic math operations, image processing tailored for the most popular workflows (size, color, blur, expand, merge, crop), flexible text handling, precision sliders, metadata and color profile-supported image saving, quick Run options via right-click (Run Group/Node), loading image folders to create batch processing workflows, and more."
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version = "0.30.2"
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version = "0.30.5"
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license = {file = "LICENSE"}
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dependencies = ["rembg, timm"]
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