xinyun/ComfyUI-KJNodes
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Fix InstanceDiffusion bboxes

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Seems it uses x1, y2, x2, y2 instead of x, y, width, height
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kijai 2024-05-04 18:12:26 +03:00
parent 4412c67aa6
commit 8ccc080bf4
2 changed files with 26 additions and 15 deletions
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2
__init__.py
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@ -114,7 +114,7 @@ NODE_CONFIG = {
"GLIGENTextBoxApplyBatchCoords": {"class": GLIGENTextBoxApplyBatchCoords}, "GLIGENTextBoxApplyBatchCoords": {"class": GLIGENTextBoxApplyBatchCoords},
"Intrinsic_lora_sampling": {"class": Intrinsic_lora_sampling, "name": "Intrinsic Lora Sampling"}, "Intrinsic_lora_sampling": {"class": Intrinsic_lora_sampling, "name": "Intrinsic Lora Sampling"},
"CreateInstanceDiffusionTracking": {"class": CreateInstanceDiffusionTracking}, "CreateInstanceDiffusionTracking": {"class": CreateInstanceDiffusionTracking},
"AppendInstanceDiffusionTracking": {"class": AppendInstanceDiffusionTracking, "name": "Append Diffusion Tracking"}, "AppendInstanceDiffusionTracking": {"class": AppendInstanceDiffusionTracking},
} }
def generate_node_mappings(node_config): def generate_node_mappings(node_config):

39
nodes/curve_nodes.py
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@ -76,8 +76,8 @@ class PlotCoordinates:
}, },
"optional": {"size_multiplier": ("FLOAT", {"default": [1.0], "forceInput": True})}, "optional": {"size_multiplier": ("FLOAT", {"default": [1.0], "forceInput": True})},
} }
RETURN_TYPES = ("IMAGE", ) RETURN_TYPES = ("IMAGE", "INT", "INT", "INT", "INT",)
RETURN_NAMES = ("images", ) RETURN_NAMES = ("images", "width", "height", "bbox_width", "bbox_height",)
FUNCTION = "append" FUNCTION = "append"
CATEGORY = "KJNodes/experimental" CATEGORY = "KJNodes/experimental"
DESCRIPTION = """ DESCRIPTION = """
@ -94,7 +94,7 @@ Plots coordinates to sequence of images using Matplotlib.
plot_image_tensor = plot_coordinates_to_tensor(coordinates, height, width, bbox_height, bbox_width, size_multiplier, text) plot_image_tensor = plot_coordinates_to_tensor(coordinates, height, width, bbox_height, bbox_width, size_multiplier, text)
return (plot_image_tensor,) return (plot_image_tensor, width, height, bbox_width, bbox_height)
class SplineEditor: class SplineEditor:
@ -665,7 +665,7 @@ bounding boxes.
for i in range(batch_size): for i in range(batch_size):
x_position, y_position = coordinates[i] x_position, y_position = coordinates[i]
position_param = (cond_pooled, int((height // 8) * size_multiplier[i]), int((width // 8) * size_multiplier[i]), (y_position - height / 2) // 8, (x_position - width / 2) // 8) position_param = (cond_pooled, int((height // 8) * size_multiplier[i]), int((width // 8) * size_multiplier[i]), (y_position - height // 2) // 8, (x_position - width // 2) // 8)
position_params_batch[i].append(position_param) # Append position_param to the correct sublist position_params_batch[i].append(position_param) # Append position_param to the correct sublist
prev = [] prev = []
@ -687,8 +687,8 @@ bounding boxes.
class CreateInstanceDiffusionTracking: class CreateInstanceDiffusionTracking:
RETURN_TYPES = ("TRACKING",) RETURN_TYPES = ("TRACKING", "INT", "INT", "INT", "INT",)
RETURN_NAMES = ("TRACKING",) RETURN_NAMES = ("tracking", "width", "height", "bbox_width", "bbox_height",)
FUNCTION = "tracking" FUNCTION = "tracking"
CATEGORY = "KJNodes/experimental" CATEGORY = "KJNodes/experimental"
DESCRIPTION = """ DESCRIPTION = """
@ -710,8 +710,7 @@ for example:
"height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}), "height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
"bbox_width": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}), "bbox_width": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
"bbox_height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}), "bbox_height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
"class_name": ("STRING", {"default": "class_name"}),
"class_name": ("STRING", {"default": "class_id"}),
"class_id": ("INT", {"default": 0,"min": 0, "max": 255, "step": 1}), "class_id": ("INT", {"default": 0,"min": 0, "max": 255, "step": 1}),
}, },
"optional": { "optional": {
@ -730,16 +729,28 @@ for example:
# Initialize a list to hold the coordinates for the current ID # Initialize a list to hold the coordinates for the current ID
id_coordinates = [] id_coordinates = []
for detection in coordinates: for coord in coordinates:
# Append the 'x' and 'y' coordinates along with bbox width/height and frame width/height to the list for the current ID x = coord['x']
id_coordinates.append([detection['x'], detection['y'], bbox_width, bbox_height, width, height]) y = coord['y']
# Calculate the top left and bottom right coordinates
top_left_x = x - bbox_width // 2
top_left_y = y - bbox_height // 2
bottom_right_x = x + bbox_width // 2
bottom_right_y = y + bbox_height // 2
# Append the top left and bottom right coordinates to the list for the current ID
id_coordinates.append([top_left_x, top_left_y, bottom_right_x, bottom_right_y, width, height])
# Append the 'x' and 'y' coordinates along with bbox width/height and frame width/height to the list for the current ID
#id_coordinates.append([coord['x'] - bbox_width // 2 , coord['y'] - bbox_height // 2, bbox_width, bbox_height, width, height])
class_id = int(class_id)
print(class_id)
# Assign the list of coordinates to the specified ID within the class_id dictionary # Assign the list of coordinates to the specified ID within the class_id dictionary
tracked[class_name][class_id] = id_coordinates tracked[class_name][class_id] = id_coordinates
print(tracked) print(tracked)
return (tracked, )
return (tracked, width, height, bbox_width, bbox_height,)
class AppendInstanceDiffusionTracking: class AppendInstanceDiffusionTracking: