diff --git a/src/mflux/flux/flux_initializer.py b/src/mflux/flux/flux_initializer.py index adab0d2..89d9a64 100644 --- a/src/mflux/flux/flux_initializer.py +++ b/src/mflux/flux/flux_initializer.py @@ -2,7 +2,7 @@ from mflux import ModelConfig from mflux.controlnet.transformer_controlnet import TransformerControlnet from mflux.controlnet.weight_handler_controlnet import WeightHandlerControlnet from mflux.flux_tools.redux.weight_handler_redux import WeightHandlerRedux -from mflux.models.depth_pro.depth_pro_initializer import DepthProInitializer +from mflux.models.depth_pro.depth_pro import DepthPro from mflux.models.redux_encoder.redux_encoder import ReduxEncoder from mflux.models.siglip_vision_transformer.siglip_vision_transformer import SiglipVisionTransformer from mflux.models.text_encoder.clip_encoder.clip_encoder import CLIPEncoder @@ -115,8 +115,8 @@ class FluxInitializer: lora_repo_id=lora_repo_id, ) - # 2. Initialize the DepthPro model and assign the weights - flux_model.depth_pro = DepthProInitializer.init() + # 2. Initialize the DepthPro model + flux_model.depth_pro = DepthPro() @staticmethod def init_redux( diff --git a/src/mflux/models/depth_pro/depth_pro.py b/src/mflux/models/depth_pro/depth_pro.py index 2a4ae70..4855785 100644 --- a/src/mflux/models/depth_pro/depth_pro.py +++ b/src/mflux/models/depth_pro/depth_pro.py @@ -7,6 +7,7 @@ import numpy as np import torch from PIL import Image +from mflux.models.depth_pro.depth_pro_initializer import DepthProInitializer from mflux.models.depth_pro.depth_pro_model import DepthProModel from mflux.post_processing.image_util import ImageUtil @@ -20,9 +21,10 @@ class DepthResult: class DepthPro(nn.Module): - def __init__(self): + def __init__(self, quantize: int | None = None): super().__init__() self.depth_pro_model = DepthProModel() + DepthProInitializer.init(self.depth_pro_model, quantize=quantize) def __call__(self, image_path: str | Path, resize: bool = True) -> DepthResult: input_array, height, width = self._pre_process(image_path) diff --git a/src/mflux/models/depth_pro/depth_pro_initializer.py b/src/mflux/models/depth_pro/depth_pro_initializer.py index ba7b8c4..7d69527 100644 --- a/src/mflux/models/depth_pro/depth_pro_initializer.py +++ b/src/mflux/models/depth_pro/depth_pro_initializer.py @@ -1,16 +1,13 @@ import mlx.nn as nn -from mflux.models.depth_pro.depth_pro import DepthPro +from mflux.models.depth_pro.depth_pro_model import DepthProModel from mflux.models.depth_pro.weight_handler_depth_pro import WeightHandlerDepthPro class DepthProInitializer: @staticmethod - def init(quantize: int | None = None) -> DepthPro: - # 1. Initialize the model - depth_pro = DepthPro() - - # 2. Load the weights + def init(depth_pro_model: DepthProModel, quantize: int | None = None) -> None: + # 1. Load the weights depth_pro_weights = WeightHandlerDepthPro.load_weights() WeightHandlerDepthPro.reposition_encoder_weights(depth_pro_weights, "upsample_latent0") WeightHandlerDepthPro.reposition_encoder_weights(depth_pro_weights, "upsample_latent1") @@ -20,11 +17,9 @@ class DepthProInitializer: WeightHandlerDepthPro.reposition_head_weights(depth_pro_weights) WeightHandlerDepthPro.reshape_transposed_convolution_weights(depth_pro_weights) - # 3. Assign the weights to the model - depth_pro.depth_pro_model.update(depth_pro_weights.weights) + # 2. Assign the weights to the model + depth_pro_model.update(depth_pro_weights.weights) - # 4. Optionally quantize the model + # 3. Optionally quantize the model if quantize: - nn.quantize(depth_pro.depth_pro_model, bits=quantize) - - return depth_pro + nn.quantize(depth_pro_model, bits=quantize) diff --git a/src/mflux/save_depth.py b/src/mflux/save_depth.py index 1e6e7fd..d38d7e2 100644 --- a/src/mflux/save_depth.py +++ b/src/mflux/save_depth.py @@ -1,5 +1,5 @@ from mflux.flux_tools.depth.depth_util import DepthUtil -from mflux.models.depth_pro.depth_pro_initializer import DepthProInitializer +from mflux.models.depth_pro.depth_pro import DepthPro from mflux.ui.cli.parsers import CommandLineParser @@ -10,7 +10,7 @@ def main(): args = parser.parse_args() # 1. Create and save the depth map - depth_pro = DepthProInitializer.init(quantize=args.quantize) + depth_pro = DepthPro(quantize=args.quantize) DepthUtil.get_or_create_depth_map(depth_pro=depth_pro, image_path=args.image_path) diff --git a/tests/depth/test_depth_pro.py b/tests/depth/test_depth_pro.py index c6d8c90..25b2b96 100644 --- a/tests/depth/test_depth_pro.py +++ b/tests/depth/test_depth_pro.py @@ -4,7 +4,7 @@ from pathlib import Path import numpy as np from PIL import Image -from mflux.models.depth_pro.depth_pro_initializer import DepthProInitializer +from mflux.models.depth_pro.depth_pro import DepthPro class TestDepthPro: @@ -17,7 +17,7 @@ class TestDepthPro: try: # Initialize DepthPro model - depth_pro = DepthProInitializer.init() + depth_pro = DepthPro() # Process the image to generate a depth map depth_result = depth_pro(str(input_image_path))