Clean up script and backward compatability.

LCAV · Sep 6, 2024 · 3d53857 · 3d53857
1 parent 7937bce
commit 3d53857
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Showing 3 changed files with 18 additions and 16 deletions.
diff --git a/lensless/utils/image.py b/lensless/utils/image.py
@@ -264,7 +264,7 @@ def get_max_val(img, nbits=None):
     max_val : int
         Maximum pixel value.
     """
-    # assert img.dtype not in FLOAT_DTYPES
+    assert img.dtype not in FLOAT_DTYPES
     if nbits is None:
         nbits = int(np.ceil(np.log2(img.max())))
 

diff --git a/lensless/utils/io.py b/lensless/utils/io.py
@@ -17,6 +17,7 @@
 from lensless.utils.image import bayer2rgb_cc, print_image_info, resize, rgb2gray, get_max_val
 from lensless.utils.plot import plot_image
 
+
 def load_mask(fp):
     mask = np.load(fp)
     return np.expand_dims(mask, axis=0)
@@ -127,7 +128,7 @@ def load_image(
         img = np.load(fp)
     elif "mat" in fp:
         mat = scipy.io.loadmat(fp)
-        img = mat['psf'][:,:,0]
+        img = mat["psf"][:, :, 0]
     else:
         img = cv2.imread(fp, cv2.IMREAD_UNCHANGED)
 
@@ -209,10 +210,6 @@ def load_image(
     else:
         if dtype is None:
             dtype = original_dtype
-        img = img.astype(np.float64)
-
-        img = img[10:260, 35:320-35]
-        img = img / np.linalg.norm(img)
 
     return img
 
@@ -390,7 +387,7 @@ def load_psf(
     if return_bg:
         return psf, bg
     else:
-        return psf.astype(np.float64)
+        return psf
 
 
 def load_data(

diff --git a/scripts/recon/hyperspectral.py b/scripts/recon/hyperspectral.py
@@ -14,27 +14,35 @@
 import time
 import pathlib as plib
 import matplotlib.pyplot as plt
-from lensless.utils.io import load_data
+from lensless.utils.io import load_image
 from lensless import (
     HyperSpectralFISTA,
 )
+import scipy
 
 
 @hydra.main(version_base=None, config_path="../../configs", config_name="defaults_recon")
 def gradient_descent(
     config,
 ):
 
-    # load mask and PSF
+    # set paths
     mask_fp = "/root/FORKS/LenslessPiCamNoa/data/mask.npy"
+    psf_fp = "/root/FORKS/LenslessPiCamNoa/data/psf.mat"
+    data_fp = "/root/FORKS/LenslessPiCamNoa/data/266_lensless.png"
+
+    ### - put your paths
+    # mask_fp = None
+    # psf_fp = None
+    # data_fp = None
+
+    # load mask and PSF
     mask = np.load(mask_fp)
     mask = np.expand_dims(mask, axis=0)
     mask = mask.astype(np.float32)
 
     # load PSF
-    import scipy
 
-    psf_fp = "/root/FORKS/LenslessPiCamNoa/data/psf.mat"
     mat = scipy.io.loadmat(psf_fp)
     psf = mat["psf"][:, :, 0]
     psf = psf.astype(np.float32)
@@ -44,9 +52,6 @@ def gradient_descent(
     psf = np.expand_dims(psf, axis=-1)  # add channels
 
     # load data
-    from lensless.utils.io import load_image
-
-    data_fp = "/root/FORKS/LenslessPiCamNoa/data/266_lensless.png"
     data = load_image(
         data_fp,
         return_float=True,
@@ -74,8 +79,8 @@ def gradient_descent(
 
     start_time = time.time()
     res = recon.apply(
-        n_iter=500,
-        disp_iter=50,
+        n_iter=100,
+        disp_iter=20,
         save=save,
         gamma=1.0,
         plot=False,