new dataset stuff

1 files changed, 31 insertions, 20 deletions

diff --git a/test.py b/test.py
index a53932d..6a5113c 100644
--- a/test.py
+++ b/test.py
@@ -6,7 +6,7 @@ from util.visualizer import Visualizer
 from util.util import mkdirs
 from util import html
 from shutil import move, copyfile
-from PIL import Image, ImageOps
+from PIL import Image, ImageOps, ImageFilter
 from skimage.transform import resize
 from scipy.misc import imresize
 from shutil import copyfile, rmtree
@@ -24,10 +24,13 @@ if __name__ == '__main__':
     opt.experiment = opt.start_img.split("/")[-1].split(".")[0]
 
     render_dir = opt.results_dir + opt.name + "/exp:" + opt.experiment + "/"
+    mov_dir = "mov/"
 
-    rmtree(render_dir)
+    if os.path.exists(render_dir):
+        rmtree(render_dir)
     mkdirs(render_dir)
-    copyfile(opt.start_img, render_dir + "frame_00000.png")
+    if opt.start_img != 'test.jpg':
+        copyfile(opt.start_img, render_dir + "frame_00000.png")
 
     data_loader = CreateRecursiveDataLoader(opt)
     dataset = data_loader.load_data()
@@ -48,11 +51,11 @@ if __name__ == '__main__':
         img_path = model.get_image_paths()
         print('%04d: process image... %s' % (i, img_path))
         ims = visualizer.save_images(webpage, visuals, img_path, aspect_ratio=opt.aspect_ratio)
+        im = visuals['fake_B']
+        save_path = render_dir + "frame_{:05d}_tmp.png".format(i+1)
+        final_path = render_dir + "frame_{:05d}.png".format(i+1)
         if dataset.name() == 'RecursiveDatasetDataLoader':
             # print(visuals.keys())
-            im = visuals['fake_B']
-            save_path = render_dir + "frame_{:05d}_tmp.png".format(i+1)
-            final_path = render_dir + "frame_{:05d}.png".format(i+1)
             # s = 256
             # p = 8
             # im = imresize(im, (s-p, s-p), interp='bicubic')
@@ -61,34 +64,42 @@ if __name__ == '__main__':
             # image_pil.save(save_path)
             # copyfile(save_path, final_path)
             if last_im is not None:
-                frac_a = 999/1000
-                frac_b = 1/1000
+                frac_a = 100/100
+                frac_b = 0/100
                 tmp_im = im.copy()
                 array_a = np.multiply(im, frac_a)
                 array_b = np.multiply(last_im, frac_b)
-                # im = np.add(array_a, array_b).astype('int8')
-                # print(im.shape, im.dtype)
-                last_im = np.roll(tmp_im, 1, axis=1)
-            else:
+                im = np.add(array_a, array_b).astype('int8')
+                #print(im.shape, im.dtype)
+                last_im = tmp_im # np.roll(tmp_im, 1, axis=1)
+            elif i < 2:
                 last_im = im.copy()
                 print(im.shape, im.dtype)
-            image_pil = Image.fromarray(im, mode='RGB')
-            image_pil.save(save_path)
-            os.rename(save_path, final_path)
+        image_pil = Image.fromarray(im, mode='RGB')
+        # image_pil.filter(ImageFilter.SHARPEN)
+        image_pil = image_pil.resize((456,256), Image.ANTIALIAS)
+        image_pil.save(save_path)
+        os.rename(save_path, final_path)
     webpage.save()
 
-    os.remove(render_dir + "frame_00000.png")
+    if os.path.exists(render_dir + "frame_00000.png"):
+        os.remove(render_dir + "frame_00000.png")
 
-    cmd = ("/usr/bin/ffmpeg", "-i", render_dir + "frame_%05d.png", "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", render_dir + opt.name + "_" + opt.experiment + ".mp4")
+    if opt.mov is not None:
+        filename = opt.mov
+        if not filename.endswith('.mp4'):
+            filename += '.mp4'
+    else:
+        filename = opt.name + "_" + opt.experiment + ".mp4"
+    cmd = ("ffmpeg", "-i", render_dir + "frame_%05d.png", "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", mov_dir + filename)
     process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
     output, error = process.communicate()
 
     print("________")
-    print("\n")
 
-    cmd = ("scp", render_dir + opt.name + "_" + opt.experiment + ".mp4", "jules@asdf.us:asdf/neural/")
+    cmd = ("scp", mov_dir + filename, "jules@asdf.us:asdf/neural/")
     process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
     output, error = process.communicate()
 
+    print("https://asdf.us/neural/" + filename)
     print("\n")
-    print("https://asdf.us/neural/" + opt.name + "_" + opt.experiment + ".mp4")