nodes/banodoco-steerable-motion
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peteromallet
2024-04-08 02:28:20 +02:00
parent 717e291247
commit a6ff35af46
7 changed files with 2843 additions and 5023 deletions
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SteerableMotion.py
+18 -13
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@@ -37,7 +37,8 @@ class BatchCreativeInterpolationNode:
"linear_strength_value": ("STRING", {"multiline": False, "default": "(0.3,0.4)"}),
"dynamic_strength_values": ("STRING", {"multiline": True, "default": "(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0)"}),
"buffer": ("INT", {"default": 4, "min": 1, "max": 16, "step": 1}),
"high_detail_mode": ("BOOLEAN", {"default": True}),
"high_detail_mode": ("BOOLEAN", {"default": True}),
"input_image_adherence": ("FLOAT", {"default": 0.4, "min": 0.0, "max": 1.0, "step": 0.01}),
},
"optional": {
"base_ipa_advanced_settings": ("ADVANCED_IPA_SETTINGS",),
@@ -45,8 +46,8 @@ class BatchCreativeInterpolationNode:
}
}
RETURN_TYPES = ("IMAGE","CONDITIONING","CONDITIONING","MODEL","SPARSE_METHOD","INT")
RETURN_NAMES = ("GRAPH","POSITIVE","NEGATIVE","MODEL","KEYFRAME_POSITIONS","BATCH_SIZE")
RETURN_TYPES = ("IMAGE","CONDITIONING","CONDITIONING","MODEL","SPARSE_METHOD","INT", "FLOAT")
RETURN_NAMES = ("GRAPH","POSITIVE","NEGATIVE","MODEL","KEYFRAME_POSITIONS","BATCH_SIZE", "SPARSECTRL_END_PERCENT")
FUNCTION = "combined_function"
CATEGORY = "Steerable-Motion"
@@ -56,7 +57,8 @@ class BatchCreativeInterpolationNode:
type_of_key_frame_influence,linear_key_frame_influence_value,
dynamic_key_frame_influence_values,type_of_strength_distribution,
linear_strength_value,dynamic_strength_values,
buffer, high_detail_mode,base_ipa_advanced_settings=None,detail_ipa_advanced_settings=None):
buffer, high_detail_mode,input_image_adherence,
base_ipa_advanced_settings=None,detail_ipa_advanced_settings=None):
def get_keyframe_positions(type_of_frame_distribution, dynamic_frame_distribution_values, images, linear_frame_distribution_value):
if type_of_frame_distribution == "dynamic":
@@ -104,19 +106,21 @@ class BatchCreativeInterpolationNode:
ipadapter_weights = ipadapter_weights if ipadapter_weights is not None else []
max_length = max(len(cn_frame_numbers), len(ipadapter_frame_numbers))
label_counter = 1 if buffer < 0 else 0
for i in range(max_length):
if i < len(cn_frame_numbers):
label = 'cn_strength_buffer' if (i == 0 and buffer > 0) else f'cn_strength_{label_counter}'
if buffer > 0:
label = 'starting_buffer' if i == 0 else ('ending_buffer' if i == len(cn_frame_numbers)-1 else f'cn_strength_{i}')
else:
label = f'cn_strength_{i}'
plt.plot(cn_frame_numbers[i], cn_weights[i], marker='o', color=colors[i % len(colors)], label=label)
if i < len(ipadapter_frame_numbers):
label = 'ipa_strength_buffer' if (i == 0 and buffer > 0) else f'ipa_strength_{label_counter}'
if buffer > 0:
label = 'starting_buffer' if i == 0 else ('ending_buffer' if i == len(ipadapter_frame_numbers)-1 else f'image_{i}')
else:
label = f'ipa_strength_{i}'
plt.plot(ipadapter_frame_numbers[i], ipadapter_weights[i], marker='x', linestyle='--', color=colors[i % len(colors)], label=label)
if label_counter == 0 or buffer < 0 or i > 0:
label_counter += 1
plt.legend()
# Adjusted generator expression for max_weight
@@ -134,8 +138,7 @@ class BatchCreativeInterpolationNode:
img_tensor = img_tensor.unsqueeze(0)
img_tensor = img_tensor.permute([0, 2, 3, 1])
return img_tensor,
return img_tensor,
def extract_strength_values(type_of_key_frame_influence, dynamic_key_frame_influence_values, keyframe_positions, linear_key_frame_influence_value):
if type_of_key_frame_influence == "dynamic":
@@ -467,7 +470,9 @@ class BatchCreativeInterpolationNode:
comparison_diagram, = plot_weight_comparison(all_cn_frame_numbers, all_cn_weights, all_ipa_frame_numbers, all_ipa_weights, buffer)
return comparison_diagram, positive, negative, model, sparse_indexes, last_key_frame_position
sparsectrl_end_percent = input_image_adherence / 1.4
return comparison_diagram, positive, negative, model, sparse_indexes, last_key_frame_position, sparsectrl_end_percent
class IpaConfigurationNode:
WEIGHT_TYPES = ["linear", "ease in", "ease out", 'ease in-out', 'reverse in-out', 'weak input', 'weak output', 'weak middle', 'strong middle']