create downscaled version of preprocessed inputs

2022-09-13 15:45:20 +00:00
parent 440444cd82
commit 701bd525d3
1 changed files with 100 additions and 0 deletions
@@ -0,0 +1,100 @@
+import os
+import tqdm
+import cv2
+import tensorflow as tf
+import scipy.interpolate as spi
+import numpy as np
+import plotly.graph_objects as go
+import plotly.express as ex
+
+os.environ["CUDA_VISIBLE_DEVICES"] = "0"
+
+
+def fill(img, mask):
+    coords = np.transpose(np.stack(np.nonzero((1 - mask))), (1,0))
+    img_idx = np.transpose(np.stack(np.nonzero((mask))), (1,0))
+    img_data = img[img_idx[:,0], img_idx[:,1], :]
+
+    interpolator =  spi.NearestNDInterpolator(x=img_idx, y=img_data)
+    img_2 = interpolator(coords)
+    res = np.zeros((512,256,3), dtype=np.float32)
+    res[coords[:,0], coords[:,1], :] = img_2
+    res[img_idx[:,0], img_idx[:,1], :] = img_data
+
+    return res
+
+
+def fill_label(img, mask):
+    coords = np.transpose(np.stack(np.nonzero((1 - mask))), (1,0))
+    img_idx = np.transpose(np.stack(np.nonzero((mask))), (1,0))
+    img_data = img[img_idx[:,0], img_idx[:,1]]
+
+    interpolator =  spi.NearestNDInterpolator(x=img_idx, y=img_data)
+    img_2 = interpolator(coords)
+    res = np.zeros((512,256), dtype=np.float32)
+    res[coords[:,0], coords[:,1]] = img_2
+    res[img_idx[:,0], img_idx[:,1]] = img_data
+
+    return res
+
+
+def downscale_uv_maps_posed_body(folder, type, size: int):
+    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+
+    frames = os.listdir(os.path.join(folder, type))
+
+    for frame in tqdm.tqdm(frames):
+        id, _ = frame.split('_')
+        img = np.load(os.path.join(folder, type, frame)); img = img['uv_posed_body_no_orient_filled']
+        down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
+        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_posed_body_no_orient_filled = down)
+
+
+def downscale_uv_maps_curv(folder, type, size):
+    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+
+    frames = os.listdir(os.path.join(folder, type))
+
+    for frame in tqdm.tqdm(frames):
+        id, _ = frame.split('_')
+        img = np.load(os.path.join(folder, type, frame)); img = img['uv_curvature_filled']
+        down = cv2.resize(img, (int(size/2), size), interpolation=cv2.INTER_NEAREST)
+        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_curvature_filled = down)
+
+
+
+def downscale_uv_maps_unposed(folder, type, size):
+    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+
+    frames = os.listdir(os.path.join(folder, type))
+
+    for frame in tqdm.tqdm(frames):
+        id, _ = frame.split('_')
+        img = np.load(os.path.join(folder, type, frame)); img = img['uv_unposed_no_shape_filled']
+        down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
+        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_unposed_no_shape_filled = down)
+
+
+
+def downscale_uv_maps_static(folder, type, size):
+    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+
+    frames = os.listdir(os.path.join(folder, type))
+
+    for frame in tqdm.tqdm(frames):
+        id, _ = frame.split('.')
+        img = np.load(os.path.join(folder, type, frame)); img = img['uv_static_filled']
+        down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
+        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_static_filled = down)
+
+
+
+if __name__ == '__main__':
+    size = 128
+    downscale_uv_maps_static(folder='/home/workspace/local-data/train_100', type='uv_static_filled', size=size)
+    downscale_uv_maps_unposed(folder='/home/workspace/local-data/train_100', type='uv_unposed_no_shape_filled', size=size)
+    downscale_uv_maps_curv(folder='/home/workspace/local-data/train_100', type='uv_curvature_filled', size=size)
+    downscale_uv_maps_posed_body(folder='/home/workspace/local-data/train_100', type='uv_posed_body_no_orient_filled', size=size)
+
+
+    print()