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-rw-r--r--scripts/builders/flow-dir.py2
-rwxr-xr-xscripts/builders/mogrify-dir.py119
-rw-r--r--scripts/flow/diff.py39
-rw-r--r--scripts/flow/flow-diff.py82
-rw-r--r--scripts/flow/flow-dir.py81
-rw-r--r--scripts/flow/flow-warp-recflow-recursive-fwd.py138
-rw-r--r--scripts/flow/flow-warp-recflow.py139
-rw-r--r--scripts/flow/flow-warp-recursive.py82
-rw-r--r--scripts/flow/flow-warp.py82
9 files changed, 762 insertions, 2 deletions
diff --git a/scripts/builders/flow-dir.py b/scripts/builders/flow-dir.py
index 620ba32..b59a0ac 100644
--- a/scripts/builders/flow-dir.py
+++ b/scripts/builders/flow-dir.py
@@ -62,7 +62,6 @@ for i,fn in enumerate(sorted(os.listdir(work_dir))):
wd = "train/"
if i == 1:
- prev_hsv = np.copy(hsv)
prev_bgr = np.copy(bgr)
continue
@@ -70,6 +69,5 @@ for i,fn in enumerate(sorted(os.listdir(work_dir))):
cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
# copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
prev = im
- prev_hsv = np.copy(hsv)
prev_bgr = np.copy(bgr)
diff --git a/scripts/builders/mogrify-dir.py b/scripts/builders/mogrify-dir.py
new file mode 100755
index 0000000..b7370f5
--- /dev/null
+++ b/scripts/builders/mogrify-dir.py
@@ -0,0 +1,119 @@
+#!/Users/user/anaconda/envs/cv/bin/python
+
+import os
+
+import sys
+sys.path.insert(0, '/Users/user/neural/pix2pix')
+from options.dataset_options import DatasetOptions
+
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import glob
+import numpy as np
+import subprocess
+import cv2
+
+opt = DatasetOptions().parse()
+
+in_dir = opt.in_dir
+out_dir = opt.out_dir
+out_base = os.path.basename(out_dir)
+
+if os.path.exists(out_dir):
+ rmtree(out_dir)
+
+os.makedirs(out_dir)
+if opt.split is True:
+ os.makedirs(out_dir + "A/")
+ os.makedirs(out_dir + "A/train/")
+ os.makedirs(out_dir + "A/test/")
+ os.makedirs(out_dir + "A/val/")
+ if opt.ab is True:
+ os.makedirs(out_dir + "B/")
+ os.makedirs(out_dir + "B/train/")
+ os.makedirs(out_dir + "B/test/")
+ os.makedirs(out_dir + "B/val/")
+
+file = open(os.path.join(out_dir, "opt.txt"), "w")
+for arg in vars(opt):
+ file.write("{}: {}\n".format(arg, getattr(opt, arg)))
+file.close()
+
+images = sorted(glob.glob(os.path.join(in_dir, '*.*g')))
+image_count = len(images)
+print("{}, {} images => {}".format(in_dir, image_count, out_base))
+for i, fn in enumerate(images):
+ pil_image = Image.open(fn).convert('RGB')
+ img = np.array(pil_image)
+ img = img[:, :, ::-1].copy()
+
+ out_file = "frame_{:05d}.png".format(i)
+
+ if i > 0 and (i % 100) == 0:
+ print("{}...".format(i))
+
+ lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
+ l, a, b = cv2.split(lab)
+
+ if opt.clahe is True:
+ clahe = cv2.createCLAHE(clipLimit=opt.clip_limit, tileGridSize=(8,8))
+ l = clahe.apply(l)
+
+ if opt.brightness_gradient is True:
+ l = np.add(l.astype('float64'), ((i / image_count) - 0.5) * opt.brightness_sigma)
+ np.clip(l, 0, 255, out=l)
+ l = l.astype('uint8')
+
+ if opt.brightness_gradient is True or opt.clahe is True:
+ limg = cv2.merge((l,a,b))
+ img = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
+
+ if opt.posterize is True:
+ img = cv2.pyrMeanShiftFiltering(img, opt.spatial_window, opt.color_window)
+ if opt.grayscale is True:
+ img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+ if opt.blur != 0:
+ img = cv2.GaussianBlur(img, (opt.blur, opt.blur), opt.blur_sigma)
+ if opt.canny is True:
+ img = cv2.Canny(img, opt.canny_lo, opt.canny_hi)
+
+ if opt.split is True:
+ if (i % 10) == 3:
+ wd = "test/"
+ elif (i % 10) == 6:
+ wd = "val/"
+ else:
+ wd = "train/"
+
+ cv2.imwrite(out_dir + "A/" + wd + out_file, img)
+ if opt.ab is True:
+ copyfile(fn, out_dir + "B/" + wd + out_file)
+
+ else:
+ cv2.imwrite(os.path.join(out_dir, out_file), img)
+
+print("{}...".format(image_count))
+
+if opt.mov:
+ print("ffmpeg...")
+ mov_file = "{}.mp4".format(out_base)
+ cmd = ("ffmpeg",
+ "-loglevel", "quiet",
+ "-i", os.path.join(out_dir, "frame_%05d.png"),
+ "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p",
+ mov_file)
+ process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
+ output, error = process.communicate()
+
+ if opt.scp:
+ print("scp...")
+ cmd = ("scp", mov_file, opt.scp)
+ process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
+ output, error = process.communicate()
+
+ print("https://asdf.us/neural/" + mov_file)
+
+ # cmd = ("mplayer", mov_file)
+ # process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
+ # output, error = process.communicate()
diff --git a/scripts/flow/diff.py b/scripts/flow/diff.py
new file mode 100644
index 0000000..555f2f7
--- /dev/null
+++ b/scripts/flow/diff.py
@@ -0,0 +1,39 @@
+#!python3
+
+from PIL import Image
+import numpy as np
+import os
+import cv2
+
+dir = 'IMG_1734/'
+diff_dir = dir + 'diff/'
+
+if not os.path.exists(diff_dir):
+ os.mkdir(diff_dir)
+
+files = sorted([i.name for i in os.scandir(dir) if os.path.isfile(dir + i.name) and not i.name.startswith('.')])
+
+last_im = None
+k = 0
+for i, fn in enumerate(files):
+ pil_image = Image.open(dir + fn).convert('RGB')
+ im = np.array(pil_image)
+
+ tmp_im = im.copy().astype('float64')
+ print("{} {}".format(i, fn))
+ if last_im is not None:
+ im = (last_im - tmp_im)
+ im = cv2.normalize(im, None, 0, 255, cv2.NORM_MINMAX)
+ image_pil = Image.fromarray(im.astype('uint8'), mode='RGB')
+ image_pil.save(diff_dir + "frame_{:05}.png".format(i))
+
+ last_im = tmp_im.astype('float64')
+
+def fade_images(a, b, n):
+ for j in range(60):
+ r = j / 60
+ im = a * (r) + b * (1-r)
+ image_pil = Image.fromarray(im.astype('uint8'), mode='RGB')
+ image_pil.save(diff_dir + "frame_{:05}.png".format(j+k))
+ k += 60
+
diff --git a/scripts/flow/flow-diff.py b/scripts/flow/flow-diff.py
new file mode 100644
index 0000000..4bd4465
--- /dev/null
+++ b/scripts/flow/flow-diff.py
@@ -0,0 +1,82 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+work_dir = "IMG_1734/"
+render_dir = "IMG_1734/flowdiff/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + 'prev/')
+os.makedirs(render_dir + 'next/')
+
+def warp_flow(img, flow):
+ h, w = flow.shape[:2]
+ flow = -flow
+ flow[:,:,0] += np.arange(w)
+ flow[:,:,1] += np.arange(h)[:,np.newaxis]
+ res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+ return res
+
+hsv = []
+prev = None
+prev_bgr = None
+gray = None
+prev_gray = None
+
+for i,fn in enumerate(sorted(os.listdir(work_dir))):
+ if os.path.basename(fn).startswith('.') or not os.path.isfile(work_dir + fn):
+ continue
+
+ # load image and convert to grayscale
+ pil_image = Image.open(work_dir + fn).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+
+ # store first frame
+ if prev_gray is None:
+ prev = im
+ prev_gray = gray
+ #hsv = np.zeros((256,512,3))
+ #hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ flow = cv2.calcOpticalFlowFarneback(prev_gray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+ #hsv[...,0] = ang * 180 / np.pi / 2
+ #hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+ #bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ #if prev_bgr is None:
+ # prev_bgr = np.copy(bgr)
+ # continue
+
+ #if (i % 10) == 3:
+ # wd = "test/"
+ #elif (i % 10) == 6:
+ # wd = "val/"
+ #else:
+ # wd = "train/"
+
+ out_prev = warp_flow(prev, flow)
+ out_next = warp_flow(im, flow)
+ ren = "frame_{:05d}.png".format(i)
+
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "prev/" + ren, out_prev)
+ cv2.imwrite(render_dir + "next/" + ren, out_next)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+ prev = im
+ prev_gray = gray
+ #prev_bgr = np.copy(bgr)
+
diff --git a/scripts/flow/flow-dir.py b/scripts/flow/flow-dir.py
new file mode 100644
index 0000000..60c1dd9
--- /dev/null
+++ b/scripts/flow/flow-dir.py
@@ -0,0 +1,81 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+work_dir = "IMG_1734/"
+render_dir = "IMG_1734/diff/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + "A/")
+os.makedirs(render_dir + "A/train/")
+os.makedirs(render_dir + "A/test/")
+os.makedirs(render_dir + "A/val/")
+os.makedirs(render_dir + "B/")
+os.makedirs(render_dir + "B/train/")
+os.makedirs(render_dir + "B/test/")
+os.makedirs(render_dir + "B/val/")
+os.makedirs(render_dir + "out/")
+
+hsv = []
+prev = None
+prev_bgr = None
+
+for i,fn in enumerate(sorted(os.listdir(work_dir))):
+ if os.path.basename(fn).startswith('.') or not os.path.isfile(work_dir + fn):
+ continue
+
+ # load image and convert to grayscale
+ pil_image = Image.open(work_dir + fn).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+
+ # store first frame
+ if prev is None:
+ prev = im
+ hsv = np.zeros((256,512,3))
+ hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ flow = cv2.calcOpticalFlowFarneback(prev, im, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ # turn into magnitude/angle
+ mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+
+ # store angle as hue
+ hsv[...,0] = ang * 180 / np.pi / 2
+
+ # store magnitude as lum
+ hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+
+ # convert this HSL to BGR
+ bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ if prev_bgr is None:
+ prev_bgr = np.copy(bgr)
+ continue
+
+ if (i % 10) == 3:
+ wd = "test/"
+ elif (i % 10) == 6:
+ wd = "val/"
+ else:
+ wd = "train/"
+
+ ren = "frame_{:05d}.png".format(i)
+
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "out/" + ren, bgr)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+ prev = im
+ prev_bgr = np.copy(bgr)
+
diff --git a/scripts/flow/flow-warp-recflow-recursive-fwd.py b/scripts/flow/flow-warp-recflow-recursive-fwd.py
new file mode 100644
index 0000000..4d15cc2
--- /dev/null
+++ b/scripts/flow/flow-warp-recflow-recursive-fwd.py
@@ -0,0 +1,138 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+from_dir = "IMG_1734/"
+to_dir = "IMG_1738/"
+render_dir = "flowwarp_transfer_cross/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + 'out_fwd_from/')
+os.makedirs(render_dir + 'out_rvr_from/')
+os.makedirs(render_dir + 'out_fwd_from_rec/')
+os.makedirs(render_dir + 'out_rvr_from_rec/')
+os.makedirs(render_dir + 'out_fwd_to/')
+os.makedirs(render_dir + 'out_rvr_to/')
+os.makedirs(render_dir + 'out_fwd_to_rec/')
+os.makedirs(render_dir + 'out_rvr_to_rec/')
+
+def warp_flow(img, flow):
+ h, w = flow.shape[:2]
+ flow = -flow
+ flow[:,:,0] += np.arange(w)
+ flow[:,:,1] += np.arange(h)[:,np.newaxis]
+ res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+ return res
+def load(path):
+ pil_image = Image.open(path).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+ return im, gray
+
+def get_files(d):
+ return sorted([i.name for i in os.scandir(d) if os.path.isfile(d + i.name) and not i.name.startswith('.') and i.name.endswith('png')])
+
+hsv = []
+prev = None
+prev_bgr = None
+gray = None
+prev_gray = None
+prev_from = None
+prev_fwd_from = None
+prev_rvr_from = None
+prev_from_gray = None
+prev_to = None
+prev_fwd_to = None
+prev_rvr_to = None
+prev_to_gray = None
+
+from_files = get_files(from_dir)
+to_files = get_files(to_dir)
+
+for i,from_fn in enumerate(from_files):
+ print(from_fn)
+ to_fn = to_files[i]
+
+ # load image and convert to grayscale
+ from_im, from_gray = load(from_dir + from_fn)
+ to_im, to_gray = load(to_dir + to_fn)
+
+ # store first frame
+ if prev_from_gray is None:
+ prev_fwd_from = from_im
+ prev_rvr_from = from_im
+ prev_from_gray = from_gray
+ prev_fwd_to = to_im
+ prev_rvr_to = to_im
+ prev_to_gray = to_gray
+ #hsv = np.zeros((256,512,3))
+ #hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ from_fwd_flow = cv2.calcOpticalFlowFarneback(prev_from_gray, from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #from_rvr_flow = cv2.calcOpticalFlowFarneback(from_gray, prev_from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #to_fwd_flow = cv2.calcOpticalFlowFarneback(prev_to_gray, to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #to_rvr_flow = cv2.calcOpticalFlowFarneback(to_gray, prev_to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #cross_fwd_flow = cv2.calcOpticalFlowFarneback(from_gray, to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #cross_rvr_flow = cv2.calcOpticalFlowFarneback(to_gray, from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+ #hsv[...,0] = ang * 180 / np.pi / 2
+ #hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+ #bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ #if prev_bgr is None:
+ # prev_bgr = np.copy(bgr)
+ # continue
+
+ #if (i % 10) == 3:
+ # wd = "test/"
+ #elif (i % 10) == 6:
+ # wd = "val/"
+ #else:
+ # wd = "train/"
+
+ fwd_flow = from_fwd_flow
+ #rvr_flow = from_rvr_flow
+ out_fwd_from = warp_flow(from_im, fwd_flow)
+ out_fwd_from_rec = warp_flow(prev_fwd_from, fwd_flow)
+ out_fwd_to = warp_flow(to_im, fwd_flow)
+ out_fwd_to_rec = warp_flow(prev_fwd_to, fwd_flow)
+
+ #out_rvr_from = warp_flow(from_im, rvr_flow)
+ #out_rvr_from_rec = warp_flow(prev_rvr_from, rvr_flow)
+ #out_rvr_to = warp_flow(to_im, rvr_flow)
+ #out_rvr_to_rec = warp_flow(prev_rvr_to, rvr_flow)
+
+ ren = "frame_{:05d}.png".format(i)
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "out_fwd_from/" + ren, out_fwd_from)
+ cv2.imwrite(render_dir + "out_fwd_from_rec/" + ren, out_fwd_from_rec)
+ cv2.imwrite(render_dir + "out_fwd_to/" + ren, out_fwd_to)
+ cv2.imwrite(render_dir + "out_fwd_to_rec/" + ren, out_fwd_to_rec)
+ #cv2.imwrite(render_dir + "out_rvr_from/" + ren, out_rvr_from)
+ #cv2.imwrite(render_dir + "out_rvr_from_rec/" + ren, out_rvr_from_rec)
+ #cv2.imwrite(render_dir + "out_rvr_to/" + ren, out_rvr_to)
+ #cv2.imwrite(render_dir + "out_rvr_to_rec/" + ren, out_rvr_to_rec)
+ #cv2.imwrite(render_dir + "next/" + ren, out_next)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+
+ prev_from_gray = from_gray
+ prev_to_gray = to_gray
+ if i > 3:
+ prev_fwd_from = out_fwd_from_rec
+ prev_fwd_to = out_fwd_to_rec
+ #prev_rvr_from = out_rvr_from_rec
+ #prev_rvr_to = out_rvr_to_rec
+ #prev_bgr = np.copy(bgr)
+
diff --git a/scripts/flow/flow-warp-recflow.py b/scripts/flow/flow-warp-recflow.py
new file mode 100644
index 0000000..5e0d7ac
--- /dev/null
+++ b/scripts/flow/flow-warp-recflow.py
@@ -0,0 +1,139 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+from_dir = "IMG_1734/"
+to_dir = "IMG_1738/"
+render_dir = "flowwarp_transfer_cross/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + 'out_fwd_from/')
+os.makedirs(render_dir + 'out_rvr_from/')
+os.makedirs(render_dir + 'out_fwd_from_rec/')
+os.makedirs(render_dir + 'out_rvr_from_rec/')
+os.makedirs(render_dir + 'out_fwd_to/')
+os.makedirs(render_dir + 'out_rvr_to/')
+os.makedirs(render_dir + 'out_fwd_to_rec/')
+os.makedirs(render_dir + 'out_rvr_to_rec/')
+
+def warp_flow(img, flow):
+ h, w = flow.shape[:2]
+ flow = -flow
+ flow[:,:,0] += np.arange(w)
+ flow[:,:,1] += np.arange(h)[:,np.newaxis]
+ res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+ return res
+def load(path):
+ pil_image = Image.open(path).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+ return im, gray
+
+def get_files(d):
+ return sorted([i.name for i in os.scandir(d) if os.path.isfile(d + i.name) and not i.name.startswith('.') and i.name.endswith('png')])
+
+hsv = []
+prev = None
+prev_bgr = None
+gray = None
+prev_gray = None
+prev_from = None
+prev_fwd_from = None
+prev_rvr_from = None
+prev_from_gray = None
+prev_to = None
+prev_fwd_to = None
+prev_rvr_to = None
+prev_to_gray = None
+
+from_files = get_files(from_dir)
+to_files = get_files(to_dir)
+
+for i,from_fn in enumerate(from_files):
+ print(from_fn)
+ to_fn = to_files[i]
+
+ # load image and convert to grayscale
+ from_im, from_gray = load(from_dir + from_fn)
+ to_im, to_gray = load(to_dir + to_fn)
+
+ # store first frame
+ if prev_from_gray is None:
+ prev_fwd_from = from_im
+ prev_rvr_from = from_im
+ prev_from_gray = from_gray
+ prev_fwd_to = to_im
+ prev_rvr_to = to_im
+ prev_to_gray = to_gray
+ #hsv = np.zeros((256,512,3))
+ #hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ from_fwd_flow = cv2.calcOpticalFlowFarneback(prev_from_gray, from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #from_rvr_flow = cv2.calcOpticalFlowFarneback(from_gray, prev_from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #to_fwd_flow = cv2.calcOpticalFlowFarneback(prev_to_gray, to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #to_rvr_flow = cv2.calcOpticalFlowFarneback(to_gray, prev_to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #cross_fwd_flow = cv2.calcOpticalFlowFarneback(from_gray, to_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+ #cross_rvr_flow = cv2.calcOpticalFlowFarneback(to_gray, from_gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+ #hsv[...,0] = ang * 180 / np.pi / 2
+ #hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+ #bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ #if prev_bgr is None:
+ # prev_bgr = np.copy(bgr)
+ # continue
+
+ #if (i % 10) == 3:
+ # wd = "test/"
+ #elif (i % 10) == 6:
+ # wd = "val/"
+ #else:
+ # wd = "train/"
+
+ fwd_flow = from_fwd_flow
+ #rvr_flow = from_rvr_flow
+ out_fwd_from = warp_flow(from_im, fwd_flow)
+ out_fwd_from_rec = warp_flow(prev_fwd_from, fwd_flow)
+ out_fwd_to = warp_flow(to_im, fwd_flow)
+ out_fwd_to_rec = warp_flow(prev_fwd_to, fwd_flow)
+
+ #out_rvr_from = warp_flow(from_im, rvr_flow)
+ #out_rvr_from_rec = warp_flow(prev_rvr_from, rvr_flow)
+ #out_rvr_to = warp_flow(to_im, rvr_flow)
+ #out_rvr_to_rec = warp_flow(prev_rvr_to, rvr_flow)
+
+ ren = "frame_{:05d}.png".format(i)
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "out_fwd_from/" + ren, out_fwd_from)
+ cv2.imwrite(render_dir + "out_fwd_from_rec/" + ren, out_fwd_from_rec)
+ cv2.imwrite(render_dir + "out_fwd_to/" + ren, out_fwd_to)
+ cv2.imwrite(render_dir + "out_fwd_to_rec/" + ren, out_fwd_to_rec)
+ #cv2.imwrite(render_dir + "out_rvr_from/" + ren, out_rvr_from)
+ #cv2.imwrite(render_dir + "out_rvr_from_rec/" + ren, out_rvr_from_rec)
+ #cv2.imwrite(render_dir + "out_rvr_to/" + ren, out_rvr_to)
+ #cv2.imwrite(render_dir + "out_rvr_to_rec/" + ren, out_rvr_to_rec)
+ #cv2.imwrite(render_dir + "next/" + ren, out_next)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+
+ prev_from_gray = from_gray
+ prev_to_gray = to_gray
+ if i > 3:
+ prev_from_gray = cv2.cvtColor(out_fwd_from_rec, cv2.COLOR_BGR2GRAY)
+ prev_fwd_from = out_fwd_from_rec
+ prev_fwd_to = out_fwd_to_rec
+ #prev_rvr_from = out_rvr_from_rec
+ #prev_rvr_to = out_rvr_to_rec
+ #prev_bgr = np.copy(bgr)
+
diff --git a/scripts/flow/flow-warp-recursive.py b/scripts/flow/flow-warp-recursive.py
new file mode 100644
index 0000000..7b08941
--- /dev/null
+++ b/scripts/flow/flow-warp-recursive.py
@@ -0,0 +1,82 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+work_dir = "IMG_1734/"
+render_dir = "IMG_1734/flowwarprecursive/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + 'prev/')
+os.makedirs(render_dir + 'next/')
+
+def warp_flow(img, flow):
+ h, w = flow.shape[:2]
+ flow = -flow
+ flow[:,:,0] += np.arange(w)
+ flow[:,:,1] += np.arange(h)[:,np.newaxis]
+ res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+ return res
+
+hsv = []
+prev = None
+prev_bgr = None
+gray = None
+prev_gray = None
+
+for i,fn in enumerate(sorted(os.listdir(work_dir))):
+ if os.path.basename(fn).startswith('.') or not os.path.isfile(work_dir + fn):
+ continue
+
+ # load image and convert to grayscale
+ pil_image = Image.open(work_dir + fn).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+
+ # store first frame
+ if prev_gray is None:
+ prev = im
+ prev_gray = gray
+ #hsv = np.zeros((256,512,3))
+ #hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ flow = cv2.calcOpticalFlowFarneback(prev_gray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+ #hsv[...,0] = ang * 180 / np.pi / 2
+ #hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+ #bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ #if prev_bgr is None:
+ # prev_bgr = np.copy(bgr)
+ # continue
+
+ #if (i % 10) == 3:
+ # wd = "test/"
+ #elif (i % 10) == 6:
+ # wd = "val/"
+ #else:
+ # wd = "train/"
+
+ out_prev = warp_flow(prev, flow)
+ #out_next = warp_flow(im, flow)
+ ren = "frame_{:05d}.png".format(i)
+
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "prev/" + ren, out_prev)
+ #cv2.imwrite(render_dir + "next/" + ren, out_next)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+ prev = out_prev
+ #prev_gray = gray
+ #prev_bgr = np.copy(bgr)
+
diff --git a/scripts/flow/flow-warp.py b/scripts/flow/flow-warp.py
new file mode 100644
index 0000000..3c7735a
--- /dev/null
+++ b/scripts/flow/flow-warp.py
@@ -0,0 +1,82 @@
+import os
+import sys
+from shutil import move, copyfile
+from PIL import Image, ImageOps
+from shutil import copyfile, rmtree
+import numpy as np
+import cv2
+
+work_dir = "IMG_1734/"
+render_dir = "IMG_1734/flowwarp/"
+
+if os.path.exists(render_dir):
+ rmtree(render_dir)
+
+os.makedirs(render_dir)
+os.makedirs(render_dir + 'prev/')
+os.makedirs(render_dir + 'next/')
+
+def warp_flow(img, flow):
+ h, w = flow.shape[:2]
+ flow = -flow
+ flow[:,:,0] += np.arange(w)
+ flow[:,:,1] += np.arange(h)[:,np.newaxis]
+ res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
+ return res
+
+hsv = []
+prev = None
+prev_bgr = None
+gray = None
+prev_gray = None
+
+for i,fn in enumerate(sorted(os.listdir(work_dir))):
+ if os.path.basename(fn).startswith('.') or not os.path.isfile(work_dir + fn):
+ continue
+
+ # load image and convert to grayscale
+ pil_image = Image.open(work_dir + fn).convert('RGB')
+ im = np.array(pil_image)
+ im = im[:, :, ::-1].copy()
+ gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+
+ # store first frame
+ if prev_gray is None:
+ prev = im
+ prev_gray = gray
+ #hsv = np.zeros((256,512,3))
+ #hsv[...,1] = 255
+ continue
+
+ # compute optical flow
+ flow = cv2.calcOpticalFlowFarneback(prev_gray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+
+ #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
+ #hsv[...,0] = ang * 180 / np.pi / 2
+ #hsv[...,2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_L2)
+ #bgr = cv2.cvtColor(hsv.astype('uint8'), cv2.COLOR_HSV2BGR)
+
+ #if prev_bgr is None:
+ # prev_bgr = np.copy(bgr)
+ # continue
+
+ #if (i % 10) == 3:
+ # wd = "test/"
+ #elif (i % 10) == 6:
+ # wd = "val/"
+ #else:
+ # wd = "train/"
+
+ out_prev = warp_flow(prev, flow)
+ #out_next = warp_flow(im, flow)
+ ren = "frame_{:05d}.png".format(i)
+
+ #cv2.imwrite(render_dir + "A/" + wd + ren, prev_bgr)
+ #cv2.imwrite(render_dir + "B/" + wd + ren, bgr)
+ cv2.imwrite(render_dir + "prev/" + ren, out_prev)
+ #cv2.imwrite(render_dir + "next/" + ren, out_next)
+ # copyfile(work_dir + fn, render_dir + "B/" + wd + ren)
+ #prev = im
+ #prev_gray = gray
+ #prev_bgr = np.copy(bgr)
+