:tada: uploaded baseline model
Browse files- README.md +69 -0
- config.json +1 -0
- weights.msgpack +3 -0
- weights.safetensors +3 -0
README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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tags:
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- jax
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- safetensors
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---
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# Baseline PerceptNet
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## Model Description
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## How to use it
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### Install the model's package from source:
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```
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git clone https://github.com/Jorgvt/paramperceptnet.git
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cd paramperceptnet
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pip install -e .
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```
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### 1.Import necessary libraries:
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```
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import json
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from huggingface_hub import hf_hub_download
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import flax
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import orbax.checkpoint
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from ml_collections import ConfigDict
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from paramperceptnet.models import Baseline as PerceptNet
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```
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### 2.Download the configuration
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```
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config_path = hf_hub_download(repo_id="Jorgvt/ppnet-baseline",
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filename="config.json")
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with open(config_path, "r") as f:
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config = ConfigDict(json.load(f))
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```
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### 3. Download the weights
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#### 3.1. Using `safetensors`
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```
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from safetensors.flax import load_file
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weights_path = hf_hub_download(repo_id="Jorgvt/ppnet-baseline",
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filename="weights.safetensors")
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variables = load_file(weights_path)
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variables = flax.traverse_util.unflatten_dict(variables, sep=".")
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params = variables["params"]
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```
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#### 3.2. Using `mgspack`
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```
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weights_path = hf_hub_download(repo_id="Jorgvt/ppnet-fully-trained",
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filename="weights.msgpack")
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with open(weights_path, "rb") as f:
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variables = orbax.checkpoint.msgpack_utils.msgpack_restore(f.read())
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variables = jax.tree_util.tree_map(lambda x: jnp.array(x), variables)
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params = variables["params"]
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```
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### 4. Use the model
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```
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from jax import numpy as jnp
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pred = model.apply({"params": params}, jnp.ones((1,384,512,3)))
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```
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config.json
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{"A_GABOR": true, "A_GDNSPATIOFREQORIENT": true, "BATCH_SIZE": 64, "CS_KERNEL_SIZE": 5, "END_LR": 0.005, "EPOCHS": 500, "GABOR_KERNEL_SIZE": 5, "GDNFINAL_KERNEL_SIZE": 1, "GDNGAUSSIAN_KERNEL_SIZE": 1, "GDN_CLIPPING": true, "INITIAL_LR": 0.01, "INIT_GABOR": false, "INIT_JH": false, "LEARNING_RATE": 0.003, "NORMALIZE_ENERGY": true, "NORMALIZE_PROB": false, "PEAK_LR": 0.04, "SEED": 42, "TRAIN_CS": false, "TRAIN_GABOR": false, "TRAIN_GDNCOLOR": false, "TRAIN_GDNGAMMA": false, "TRAIN_GDNGAUSSIAN": false, "TRAIN_JH": false, "TRAIN_ONLY_LAST_GDN": true, "USE_BIAS": false, "USE_GAMMA": false, "WARMUP_EPOCHS": 15, "ZERO_MEAN": true}
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weights.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:77fd6911c18eb9813a955b568682809855201e4396889f34774920047f721e5d
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size 30395788
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weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6e0876beebc3fe5bff1ae63f484ce1ab25a90dbf624757f4962c888ef9d808a8
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size 30396424
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