attempt to update cache

ultralytics/data/base.py

@@ -81,20 +81,19 @@ class BaseDataset(Dataset):
         if self.rect:
             assert self.batch_size is not None
             self.set_rectangle()
-        if isinstance(cache, str):
-            cache = cache.lower()
-
         # Buffer thread for mosaic images
         self.buffer = []  # buffer size = batch size
         self.max_buffer_length = min((self.ni, self.batch_size * 8, 1000)) if self.augment else 0
 
         # Cache images
+        if isinstance(cache, str):
+            cache = cache.lower()
         if cache == "ram" and not self.check_cache_ram():
             cache = False
         self.ims, self.im_hw0, self.im_hw = [None] * self.ni, [None] * self.ni, [None] * self.ni
         self.npy_files = [Path(f).with_suffix(".npy") for f in self.im_files]
-        if cache:
-            self.cache_images(cache)
+        self.cache_disk = cache == "disk"  # cache images on hard drive as uncompressed *.npy files
+        self.cache_ram = cache and not self.cache_disk  # cache images into RAM
 
         # Transforms
         self.transforms = self.build_transforms(hyp=hyp)
@@ -149,16 +148,15 @@ class BaseDataset(Dataset):
     def load_image(self, i, rect_mode=True):
         """Loads 1 image from dataset index 'i', returns (im, resized hw)."""
         im, f, fn = self.ims[i], self.im_files[i], self.npy_files[i]
-        if im is None:  # not cached in RAM
-            if fn.exists():  # load npy
-                try:
-                    im = np.load(fn)
-                except Exception as e:
-                    LOGGER.warning(f"{self.prefix}WARNING ⚠️ Removing corrupt *.npy image file {fn} due to: {e}")
-                    Path(fn).unlink(missing_ok=True)
-                    im = cv2.imread(f)  # BGR
-            else:  # read image
-                im = cv2.imread(f)  # BGR
+        if im is None:
+            if self.cache_ram:
+                im = self.ims[i] = cv2.imread(f)
+            elif self.cache_disk:
+                if not fn.exists():
+                    np.save(fn.as_posix(), cv2.imread(f), allow_pickle=False)
+                im = np.load(fn)
+            else:
+                im = cv2.imread(f)
             if im is None:
                 raise FileNotFoundError(f"Image Not Found {f}")
 
@@ -183,28 +181,6 @@ class BaseDataset(Dataset):
 
         return self.ims[i], self.im_hw0[i], self.im_hw[i]
 
-    def cache_images(self, cache):
-        """Cache images to memory or disk."""
-        b, gb = 0, 1 << 30  # bytes of cached images, bytes per gigabytes
-        fcn = self.cache_images_to_disk if cache == "disk" else self.load_image
-        with ThreadPool(NUM_THREADS) as pool:
-            results = pool.imap(fcn, range(self.ni))
-            pbar = TQDM(enumerate(results), total=self.ni, disable=LOCAL_RANK > 0)
-            for i, x in pbar:
-                if cache == "disk":
-                    b += self.npy_files[i].stat().st_size
-                else:  # 'ram'
-                    self.ims[i], self.im_hw0[i], self.im_hw[i] = x  # im, hw_orig, hw_resized = load_image(self, i)
-                    b += self.ims[i].nbytes
-                pbar.desc = f"{self.prefix}Caching images ({b / gb:.1f}GB {cache})"
-            pbar.close()
-
-    def cache_images_to_disk(self, i):
-        """Saves an image as an *.npy file for faster loading."""
-        f = self.npy_files[i]
-        if not f.exists():
-            np.save(f.as_posix(), cv2.imread(self.im_files[i]), allow_pickle=False)
-
     def check_cache_ram(self, safety_margin=0.5):
         """Check image caching requirements vs available memory."""
         b, gb = 0, 1 << 30  # bytes of cached images, bytes per gigabytes