plotting updates

check.py

@@ -46,24 +46,27 @@ def create_circle(ckpt: str, fname: str, dpi: int = 150):
         M = ckpt
 
     rgb_tensor, _ = extract_colors()
+    rgb_tensor = preprocess_data(rgb_tensor)
     preds = M(rgb_tensor.to(M.device))
-    plot_preds(preds, fname=fname, dpi=dpi)
-
+    plot_preds(preds, rgb_tensor.detach().cpu().numpy(), fname=fname, dpi=dpi)
 
-def plot_preds(preds, fname: str, roll: bool = False, dpi: int = 150, figsize=(3, 3)):
-    rgb_tensor, _ = extract_colors()
-    rgb_values = rgb_tensor.detach().numpy()
-    rgb_tensor = preprocess_data(rgb_tensor)
 
+def plot_preds(
+    preds, rgb_values, fname: str, roll: bool = False, dpi: int = 150, figsize=(3, 3)
+):
     if isinstance(preds, torch.Tensor):
         preds = preds.detach().cpu().numpy()
     sorted_inds = np.argsort(preds.ravel())
-    colors = rgb_values[sorted_inds]
+    colors = rgb_values[sorted_inds, :]
     if roll:
         # find white in colors, put it first.
         white = np.array([1, 1, 1])
-        white_idx = np.where((colors == white).all(axis=1))[0][0]
-        colors = np.roll(colors, -white_idx, axis=0)
+        white_idx = np.where((colors == white).all(axis=1))
+        if white_idx:
+            white_idx = white_idx[0][0]
+            colors = np.roll(colors, -white_idx, axis=0)
+        else:
+            print("no white, skipping")
         # print(white_idx, colors[:2])
 
     N = len(colors)
@@ -76,10 +79,13 @@ def plot_preds(preds, fname: str, roll: bool = False, dpi: int = 150, figsize=(3
 
     for i in range(N):
         ax.bar(
+            # 2 * np.pi * preds[i],
             theta[i],
-            1,
+            height=1,
             width=width,
             edgecolor="none",
+            # facecolor=[rgb_values[i][1]]*3,
+            # facecolor=rgb_values[i],
             facecolor=colors[i],
             bottom=0.0,
             zorder=1,

hsv.py

@@ -7,8 +7,11 @@ from utils import extract_colors
 if __name__ == "__main__":
     rgb_tensor, _ = extract_colors()
     xkcd_rgb = rgb_tensor.numpy()
+    # xkcd_rgb = np.random.rand(1000, 3)
     xkcd_hsv = rgb_to_hsv(xkcd_rgb)
-    plot_preds(xkcd_hsv[:, 0], fname="hsv", roll=True, dpi=150, figsize=(6, 6))
+    plot_preds(
+        xkcd_hsv[:, 0], xkcd_rgb, fname="hsv", roll=False, dpi=300, figsize=(6, 6)
+    )
     rgb = np.eye(3)
     print("Pure RGB in Hue-Space:")
     print(rgb_to_hsv(rgb)[:, 0])

main.py

@@ -72,13 +72,13 @@ if __name__ == "__main__":
 
     save_img_callback = SaveImageCallback(
         save_interval=0,
-        final_dir="out",
+        final_dir=None,
     )
 
     # Initialize data loader with parsed arguments
     # named_data_loader also has grayscale extras. TODO: remove unnamed
     train_dataloader = create_dataloader(
-        N=1e7,
+        N=1e5,
         batch_size=args.bs,
         shuffle=True,
         num_workers=args.num_workers,

out/index.html

@@ -74,7 +74,7 @@
 
             for (var i = 0; i < 100; i++) { // Changed from i <= 100 to i < 100
                 let imageName;
-                if (i == 21) {
+                if (i == -21) {
                     imageName = 'hsv.png';
                 } else {
                     imageName = 'v' + i + '.png';