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Update README.md

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  1. README.md +8 -1
README.md CHANGED
@@ -47,14 +47,18 @@ Here is how to use this model:
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  ```python
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  from skimage import io, segmentation, morphology, measure, exposure
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  from sribd_cellseg_models import MultiStreamCellSegModel,ModelConfig
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  import numpy as np
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  import tifffile as tif
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  import requests
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  import torch
 
 
 
 
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- img_name = 'cell_00023.tiff'
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  def normalize_channel(img, lower=1, upper=99):
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  non_zero_vals = img[np.nonzero(img)]
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  percentiles = np.percentile(non_zero_vals, [lower, upper])
@@ -86,5 +90,8 @@ my_model.__init__(ModelConfig())
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  my_model.load_checkpoints(checkpoints)
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  with torch.no_grad():
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  output = my_model(pre_img_data)
 
 
 
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  ```
 
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  ```python
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+
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  from skimage import io, segmentation, morphology, measure, exposure
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  from sribd_cellseg_models import MultiStreamCellSegModel,ModelConfig
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  import numpy as np
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  import tifffile as tif
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  import requests
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  import torch
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+ from PIL import Image
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+ from overlay import visualize_instances_map
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+ import cv2
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+ img_name = 'test_images/cell_00551.tiff'
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  def normalize_channel(img, lower=1, upper=99):
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  non_zero_vals = img[np.nonzero(img)]
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  percentiles = np.percentile(non_zero_vals, [lower, upper])
 
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  my_model.load_checkpoints(checkpoints)
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  with torch.no_grad():
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  output = my_model(pre_img_data)
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+ overlay = visualize_instances_map(pre_img_data,star_label)
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+ cv2.imwrite('prediction.png', cv2.cvtColor(overlay, cv2.COLOR_RGB2BGR))
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+
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  ```