update config since changes in model architecture
Browse files- README.md +4 -4
- assets/tiger.jpg +0 -0
- config.json +130 -19
README.md
CHANGED
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@@ -8,7 +8,7 @@ pipeline_tag: depth-estimation
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Install the required libraries:
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```bash
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pip install -q numpy pillow torch torchvision
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-
pip install -q git+https://github.com/geetu040/transformers.git@depth-pro
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```
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Import the required libraries:
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@@ -22,14 +22,14 @@ from huggingface_hub import hf_hub_download
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import matplotlib.pyplot as plt
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# custom installation from this PR: https://github.com/huggingface/transformers/pull/34583
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-
# !pip install git+https://github.com/geetu040/transformers.git@depth-pro
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from transformers import DepthProConfig, DepthProImageProcessorFast, DepthProForDepthEstimation
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```
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Load the model and image processor:
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```py
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checkpoint = "geetu040/DepthPro"
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-
revision = "
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image_processor = DepthProImageProcessorFast.from_pretrained(checkpoint, revision=revision)
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model = DepthProForDepthEstimation.from_pretrained(checkpoint, revision=revision)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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@@ -40,7 +40,7 @@ Inference:
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```py
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# inference
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url = "https://huggingface.co/
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image = Image.open(requests.get(url, stream=True).raw)
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image = image.convert("RGB")
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Install the required libraries:
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```bash
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pip install -q numpy pillow torch torchvision
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+
pip install -q git+https://github.com/geetu040/transformers.git@depth-pro#egg=transformers
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```
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Import the required libraries:
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import matplotlib.pyplot as plt
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# custom installation from this PR: https://github.com/huggingface/transformers/pull/34583
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+
# !pip install git+https://github.com/geetu040/transformers.git@depth-pro#egg=transformers
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from transformers import DepthProConfig, DepthProImageProcessorFast, DepthProForDepthEstimation
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```
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Load the model and image processor:
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```py
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checkpoint = "geetu040/DepthPro"
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+
revision = "main"
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image_processor = DepthProImageProcessorFast.from_pretrained(checkpoint, revision=revision)
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model = DepthProForDepthEstimation.from_pretrained(checkpoint, revision=revision)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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```py
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# inference
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+
url = "https://huggingface.co/geetu040/DepthPro/resolve/main/assets/tiger.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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image = image.convert("RGB")
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assets/tiger.jpg
ADDED
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config.json
CHANGED
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@@ -1,14 +1,92 @@
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{
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-
"apply_layernorm": true,
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"architectures": [
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"DepthProForDepthEstimation"
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],
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"
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"fusion_hidden_size": 256,
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"
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"initializer_range": 0.02,
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"intermediate_feature_dims": [
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256,
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@@ -18,18 +96,52 @@
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11,
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5
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],
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"
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"layerscale_value": 1.0,
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-
"mlp_ratio": 4,
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"model_type": "depth_pro",
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"num_attention_heads": 16,
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"num_channels": 3,
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"num_fov_head_layers": 2,
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"
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-
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"patch_size": 384,
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-
"qkv_bias": true,
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-
"reshape_hidden_states": true,
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"scaled_images_feature_dims": [
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1024,
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1024,
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0.5,
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1
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],
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-
"torch_dtype": "
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-
"transformers_version": "4.
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"use_batch_norm_in_fusion_residual": false,
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"use_bias_in_fusion_residual": true,
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"use_fov_model": true
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"use_swiglu_ffn": false
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}
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{
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"architectures": [
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"DepthProForDepthEstimation"
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],
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"fov_model_config": {
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"hidden_size": 1024,
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"image_size": 384,
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"model_type": "dinov2",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"out_features": [
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"stage24"
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],
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"out_indices": [
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24
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],
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"patch_size": 16,
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4",
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"stage5",
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"stage6",
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"stage7",
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"stage8",
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"stage9",
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"stage10",
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"stage11",
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"stage12",
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"stage13",
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"stage14",
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"stage15",
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"stage16",
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"stage17",
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"stage18",
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"stage19",
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"stage20",
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"stage21",
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"stage22",
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"stage23",
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"stage24"
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],
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"use_mask_token": false
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},
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"fusion_hidden_size": 256,
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"image_model_config": {
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"hidden_size": 1024,
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"image_size": 384,
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"model_type": "dinov2",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"out_features": [
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"stage24"
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],
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"out_indices": [
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24
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],
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"patch_size": 16,
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4",
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"stage5",
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"stage6",
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"stage7",
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"stage8",
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"stage9",
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"stage10",
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"stage11",
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"stage12",
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"stage13",
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"stage14",
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"stage15",
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"stage16",
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"stage17",
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"stage18",
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"stage19",
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"stage20",
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"stage21",
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"stage22",
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"stage23",
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"stage24"
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],
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"use_mask_token": false
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},
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"initializer_range": 0.02,
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"intermediate_feature_dims": [
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256,
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11,
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5
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],
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"merge_padding_value": 3,
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"model_type": "depth_pro",
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"num_fov_head_layers": 2,
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"patch_model_config": {
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"hidden_size": 1024,
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"image_size": 384,
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"model_type": "dinov2",
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+
"num_attention_heads": 16,
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"num_hidden_layers": 24,
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+
"out_features": [
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+
"stage24"
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],
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+
"out_indices": [
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+
24
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+
],
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"patch_size": 16,
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+
"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4",
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"stage5",
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+
"stage6",
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"stage7",
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"stage8",
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"stage9",
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+
"stage10",
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+
"stage11",
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+
"stage12",
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+
"stage13",
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+
"stage14",
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+
"stage15",
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+
"stage16",
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+
"stage17",
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+
"stage18",
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"stage19",
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"stage20",
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"stage21",
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"stage22",
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"stage23",
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+
"stage24"
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],
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"use_mask_token": false
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},
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"patch_size": 384,
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"scaled_images_feature_dims": [
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1024,
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1024,
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0.5,
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1
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],
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+
"torch_dtype": "float16",
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"transformers_version": "4.49.0.dev0",
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"use_batch_norm_in_fusion_residual": false,
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"use_bias_in_fusion_residual": true,
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+
"use_fov_model": true
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}
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