Implement Compass Image Loader node with dynamic directory discovery and autocomplete

compass_image_loader.py

@@ -0,0 +1,157 @@
+from PIL import Image
+import folder_paths
+import os
+import torch
+import numpy as np
+
+
+VALID_DIRECTIONS = {"n", "ne", "e", "se", "s", "sw", "w", "nw"}
+VALID_MODALITIES = {"image", "depth", "openpose"}
+
+
+def _discover_directories():
+    base_dir = folder_paths.get_input_directory()
+    if not os.path.exists(base_dir):
+        return []
+
+    candidates = set()
+    for root, subdirs, _ in os.walk(base_dir, followlinks=True):
+        current_path = root[os.path.dirname(root) + 1:]
+        sub_dirs_lower = {s.lower() for s in subdirs}
+        if VALID_DIRECTIONS & sub_dirs_lower or VALID_MODALITIES & sub_dirs_lower:
+            candidates.add(current_path)
+
+    return sorted(candidates)
+
+
+class CompassImageLoader:
+    CATEGORY = "image/loaders"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        directories = _discover_directories()
+        return {
+            "required": {
+                "directory": (directories if directories else ["(none found)"],),
+                "direction": (["", "n", "ne", "e", "se", "s", "sw", "w", "nw"],),
+                "modality": (["image", "depth", "openpose"],),
+                "frame": ("STRING", {"default": ""}),
+                "width": ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+                "height": ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE", "STRING", "INT", "INT", "INT")
+    RETURN_NAMES = ("IMAGE", "path", "width", "height", "frame_count")
+    FUNCTION = "load_images"
+
+    def load_images(self, directory, direction, modality, frame=None, width=0, height=0):
+        base_dir = folder_paths.get_input_directory()
+
+        if direction and direction.strip():
+            target_dir = os.path.join(base_dir, directory, direction, modality)
+        else:
+            target_dir = os.path.join(base_dir, directory, modality)
+
+        if not os.path.isdir(target_dir):
+            raise RuntimeError(f"Compass directory not found: {target_dir}")
+
+        supported_extensions = {"png", "jpg", "jpeg", "webp", "bmp", "gif", "tiff"}
+        files = [
+            f for f in sorted(os.listdir(target_dir))
+            if os.path.isfile(os.path.join(target_dir, f)) and f.split(".")[-1].lower() in supported_extensions
+        ]
+
+        if not files:
+            raise RuntimeError(f"No images found in: {target_dir}")
+
+        if frame is None or str(frame).strip() == "":
+            selected_files = files
+            output_path = target_dir
+        else:
+            try:
+                index = int(str(frame).strip())
+            except (ValueError, TypeError):
+                raise RuntimeError(f"Invalid frame number: '{frame}'. Must be an integer.")
+
+            if index < 0 or index >= len(files):
+                raise RuntimeError(
+                    f"Frame index {index} out of bounds. Found {len(files)} images in {target_dir}."
+                )
+
+            selected_files = [files[index]]
+            output_path = os.path.join(target_dir, files[index])
+
+        tensors = []
+        final_w, final_h = 0, 0
+
+        for filename in selected_files:
+            filepath = os.path.join(target_dir, filename)
+            image = Image.open(filepath).convert("RGB")
+            orig_w, orig_h = image.size
+
+            if width == 0 and height == 0:
+                pass
+            elif width > 0 and height == 0:
+                fw = width
+                fh = int(orig_h * (width / orig_w))
+                image = image.resize((fw, fh), Image.Resampling.LANCZOS)
+            elif height > 0 and width == 0:
+                fh = height
+                fw = int(orig_w * (height / orig_h))
+                image = image.resize((fw, fh), Image.Resampling.LANCZOS)
+            else:
+                scale = max(width / orig_w, height / orig_h)
+                new_w = int(orig_w * scale)
+                new_h = int(orig_h * scale)
+                image = image.resize((new_w, new_h), Image.Resampling.LANCZOS)
+                left = (new_w - width) // 2
+                top = (new_h - height) // 2
+                right = left + width
+                bottom = top + height
+                image = image.crop((left, top, right, bottom))
+
+            final_w, final_h = image.size[0], image.size[1]
+
+            np_image = np.array(image).astype(np.float32) / 255.0
+            tensor = torch.from_numpy(np_image)[None,]
+            tensors.append(tensor)
+
+        if len(tensors) == 1:
+            image_batch = tensors[0]
+        else:
+            image_batch = torch.cat(tensors, dim=0)
+
+        return (image_batch, output_path, final_w, final_h, len(selected_files))
+
+    @classmethod
+    def IS_CHANGED(cls, directory, direction, modality, frame=None, width=0, height=0):
+        base_dir = folder_paths.get_input_directory()
+
+        if direction and direction.strip():
+            target_dir = os.path.join(base_dir, directory, direction, modality)
+        else:
+            target_dir = os.path.join(base_dir, directory, modality)
+
+        import hashlib
+
+        m = hashlib.sha256()
+        m.update(f"{directory}:{direction}:{modality}:{frame}:{width}:{height}".encode("utf-8"))
+        if not os.path.isdir(target_dir):
+            return ""
+
+        supported_extensions = {"png", "jpg", "jpeg", "webp", "bmp", "gif", "tiff"}
+        files = [
+            f for f in sorted(os.listdir(target_dir))
+            if os.path.isfile(os.path.join(target_dir, f)) and f.split(".")[-1].lower() in supported_extensions
+        ]
+
+        if frame is None or str(frame).strip() == "":
+            m.update(":".join(files).encode("utf-8"))
+        else:
+            try:
+                index = int(str(frame).strip())
+                filepath = os.path.join(target_dir, files[index])
+                with open(filepath, "rb") as f:
+                    m.update(f.read(65536))
+            except (ValueError, IndexErro