Soumya Ranjan Mohanty srmsoumya

## inference.ipynb

      
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                srmsoumya
                / inference.ipynb
            
            
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              January 14, 2022 08:13
            
              
                Inference script of TF segmentation model
              
          
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## devg-tfserve-inference-lite.ipynb

      
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                srmsoumya
                / devg-tfserve-inference-lite.ipynb
            
            
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              February 10, 2022 06:49
            
          
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## 2022-02-07_cmr-stac-api.ipynb

      
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                srmsoumya
                / 2022-02-07_cmr-stac-api.ipynb
            
            
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              May 28, 2024 12:59
            
              
                # Create Monthly NDVI composites using Harmonized Landsat Sentinel (HLS) data from NASA CMR STAC api using `pystac_client` & `stackstac` 
              
          
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## timeseries-lulc-model.py
import torch
import torch.nn as nn
import torch.nn.functional as F


def _conv(ni, nf, ks):
    return nn.Conv1d(ni, nf, kernel_size=ks, stride=1, padding=ks // 2)


def _conv_layer(ni, nf, ks, drop=0.0):

## net.py
import os
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
import lightning as L


# Generate a synthetic dataset
def generate_data(num_samples):
    # Generate random integers

## inference.py
import yaml
import numpy as np
import rasterio as rio
import torch
from prithvi import MaskedAutoencoderViT
from huggingface_hub import hf_hub_download

# Constants
REPO_ID = "ibm-nasa-geospatial/Prithvi-100M"
CONFIG = "Prithvi_100M_config.yaml"
	import torch
	import torch.nn as nn
	import torch.nn.functional as F


	def _conv(ni, nf, ks):
	return nn.Conv1d(ni, nf, kernel_size=ks, stride=1, padding=ks // 2)


	def _conv_layer(ni, nf, ks, drop=0.0):
	import os
	import torch
	from torch import nn
	from torch.utils.data import DataLoader, TensorDataset
	import lightning as L


	# Generate a synthetic dataset
	def generate_data(num_samples):
	# Generate random integers
	import yaml
	import numpy as np
	import rasterio as rio
	import torch
	from prithvi import MaskedAutoencoderViT
	from huggingface_hub import hf_hub_download

	# Constants
	REPO_ID = "ibm-nasa-geospatial/Prithvi-100M"
	CONFIG = "Prithvi_100M_config.yaml"