remove dependency on scipy.misc.imresize

whh14 · Jul 20, 2021 · 1c94ea8 · 1c94ea8
1 parent 983013c
commit 1c94ea8
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Showing 5 changed files with 11 additions and 16 deletions.
diff --git a/COTR/cameras/capture.py b/COTR/cameras/capture.py
@@ -13,7 +13,6 @@
 import numpy as np
 import imageio
 from PIL import Image
-from scipy import misc
 
 
 def crop_center_max(img):
@@ -101,4 +100,4 @@ def pad_to_square_np(img, till_divisible_by=1, return_starts=False):
 
 def stretch_to_square_np(img):
     size = max(*img.shape[:2])
-    return misc.imresize(img, (size, size), interp='bilinear')
+    return cv2.resize(img, (size, size), interpolation=cv2.INTER_LINEAR)
diff --git a/COTR/inference/inference_helper.py b/COTR/inference/inference_helper.py
@@ -5,7 +5,6 @@
 import torch
 from torchvision.transforms import functional as tvtf
 from tqdm import tqdm
-from scipy import misc
 
 from COTR.utils import utils, debug_utils
 from COTR.utils.constants import MAX_SIZE
@@ -16,6 +15,7 @@
 THRESHOLD_PIXELS_RELATIVE = 0.02
 BASE_ZOOM = 1.0
 THRESHOLD_AREA = 0.02
+LARGE_GPU = True
 
 
 def find_prediction_loop(arr):
@@ -103,12 +103,11 @@ def get_patch_centered_at(img, pos, scale=1.0, return_content=True, img_shape=No
 
 def cotr_patch_flow_exhaustive(model, patches_a, patches_b):
     def one_pass(model, img_a, img_b):
-        LARGE_GPU = True
         device = next(model.parameters()).device
         img_a = crop_center_max_np(img_a)
         img_b = crop_center_max_np(img_b)
-        img_a = misc.imresize(img_a, (MAX_SIZE, MAX_SIZE), interp='bilinear')
-        img_b = misc.imresize(img_b, (MAX_SIZE, MAX_SIZE), interp='bilinear')
+        img_a = cv2.resize(img_a, (MAX_SIZE, MAX_SIZE), interpolation=cv2.INTER_LINEAR)
+        img_b = cv2.resize(img_b, (MAX_SIZE, MAX_SIZE), interpolation=cv2.INTER_LINEAR)
         img = two_images_side_by_side(img_a, img_b)
         img = tvtf.normalize(tvtf.to_tensor(img), (0.485, 0.456, 0.406), (0.229, 0.224, 0.225)).float()[None]
         img = img.to(device)

diff --git a/COTR/inference/refinement_task.py b/COTR/inference/refinement_task.py
@@ -3,9 +3,8 @@
 import numpy as np
 import torch
 from torchvision.transforms import functional as tvtf
-import scipy
-from scipy import misc
 import imageio
+import cv2
 
 from COTR.inference.inference_helper import BASE_ZOOM, THRESHOLD_PIXELS_RELATIVE, get_patch_centered_at, two_images_side_by_side, find_prediction_loop
 from COTR.utils import debug_utils, utils
@@ -115,8 +114,8 @@ def get_task(self):
         assert img_from.shape[0] == img_from.shape[1]
         assert img_to.shape[0] == img_to.shape[1]
 
-        img_from = misc.imresize(img_from, (MAX_SIZE, MAX_SIZE), interp='bilinear')
-        img_to = misc.imresize(img_to, (MAX_SIZE, MAX_SIZE), interp='bilinear')
+        img_from = cv2.resize(img_from, (MAX_SIZE, MAX_SIZE), interpolation=cv2.INTER_LINEAR)
+        img_to = cv2.resize(img_to, (MAX_SIZE, MAX_SIZE), interpolation=cv2.INTER_LINEAR)
         img = two_images_side_by_side(img_from, img_to)
         img = tvtf.normalize(tvtf.to_tensor(img), (0.485, 0.456, 0.406), (0.229, 0.224, 0.225)).float()
 

diff --git a/COTR/utils/utils.py b/COTR/utils/utils.py
@@ -9,7 +9,6 @@
 import torch
 import cv2
 import matplotlib.pyplot as plt
-from scipy.misc import imresize
 
 
 '''
@@ -32,15 +31,15 @@ def fix_randomness(seed=42):
     np.random.seed(seed)
 
 
-def float_image_resize(img, shape, interp='bilinear'):
+def float_image_resize(img, shape, interp=cv2.INTER_LINEAR):
     missing_channel = False
     if len(img.shape) == 2:
         missing_channel = True
         img = img[..., None]
     layers = []
     img = img.transpose(2, 0, 1)
     for l in img:
-        l = imresize(l, shape, interp=interp, mode='F')
+        l = cv2.resize(l, shape, interpolation=interp)
         layers.append(l)
     if missing_channel:
         return np.stack(layers, axis=-1)[..., 0]
@@ -175,8 +174,8 @@ def visualize_corrs(img1, img2, corrs, mask=None):
     if w > max_w:
         scale1 *= max_w / w
         scale2 *= max_w / w
-    img1 = imresize(img1, scale1)
-    img2 = imresize(img2, scale2)
+    img1 = cv2.resize(img1, (0,0), fx=scale1, fy=scale1)
+    img2 = cv2.resize(img2, (0,0), fx=scale2, fy=scale2)
 
     x1, x2 = corrs[:, :2], corrs[:, 2:]
     h1, w1 = img1.shape[:2]

diff --git a/readme.md b/readme.md
@@ -15,7 +15,6 @@ Our implementation is based on PyTorch. Install the conda environment by: `conda
 
 Activate the environment by: `conda activate cotr_env`.
 
-Notice that we use `scipy=1.2.1` .
 
 
 ### 2. Download the pretrained weights
Original file line number	Diff line number	Diff line change
Expand Up		@@ -15,7 +15,6 @@ Our implementation is based on PyTorch. Install the conda environment by: `conda

		Activate the environment by: `conda activate cotr_env`.

		Notice that we use `scipy=1.2.1` .


		### 2. Download the pretrained weights
Expand Down