Fix pipeline

.flake8

@@ -1,3 +1,3 @@
 [flake8]
 max-line-length = 88
-extend-ignore = E203
+extend-ignore = E203, F722, F821

thermo_nerf/flir_thermal_images/custom_flir.py

@@ -3,11 +3,10 @@
 
 import numpy as np
 import pandas as pd
+from FlirImageExtractor.flir_image_extractor import FlirImageExtractor
 from matplotlib import cm
 from PIL import Image
 
-from FlirImageExtractor.flir_image_extractor import FlirImageExtractor
-
 
 def get_min_max_temperatures(path_to_csv_files: str) -> tuple[float, float]:
     """
@@ -87,10 +86,6 @@ def save_normalised_thermal_images(
                 self.absolute_max_temperature,
             )
 
-            # temperature = temperature.reshape(640, 480)
-            # image = Image.fromarray(temperature)
-            # image.save(Path(path_to_thermal_images_curated, Path(path).stem + ".tiff"))
-
             gray_scale_image = temperature.reshape(640, 480).astype("uint8")
 
             Image.fromarray(gray_scale_image, mode="L").save(

thermo_nerf/thermal_nerf/thermal_dataparser.py

@@ -222,7 +222,8 @@ def _generate_dataparser_outputs(self, split: str = "train") -> DataparserOutput
 
         poses[:, :3, 3] *= scale_factor
 
-        # Choose image_filenames and poses based on split, but after auto orient and scaling the poses.
+        # Choose image_filenames and poses based on split, but after auto orient
+        # and scaling the poses.
         image_filenames = [image_filenames[i] for i in indices]
 
         thermal_filenames = (

thermo_nerf/thermal_nerf/thermal_field_head.py

@@ -62,7 +62,8 @@ def forward(
         """
         if not self.net:
             raise SystemError(
-                "in_dim not set. Must be provided to constructor, or set_in_dim() should be called."
+                "in_dim not set. Must be provided to constructor, or set_in_dim()"
+                " should be called."
             )
         out_tensor = self.net(in_tensor)
         if self.activation:

thermo_nerf/thermal_nerf/thermal_renderer.py

@@ -33,7 +33,8 @@ def combine_thermal(
         num_rays: Optional[int] = None,
     ) -> Float[Tensor, "*bs 3"]:
         """Composite samples along ray and render color image.
-        If background color is random, no BG color is added - as if the background was black!
+        If background color is random, no BG color is added - as if the background was
+        black!
 
         Args:
             thermal: thermal for each sample