From 1f36e83c9d728caaa4b67f0dbd10bfe3783fc73a Mon Sep 17 00:00:00 2001
From: Grant Sanderson <grant@3blue1brown.com>
Date: Tue, 24 Nov 2020 13:29:44 -0800
Subject: [PATCH] Delete defunct functionality

---
 manimlib/scene/scene_from_video.py | 53 ------------------------------
 1 file changed, 53 deletions(-)
 delete mode 100644 manimlib/scene/scene_from_video.py

diff --git a/manimlib/scene/scene_from_video.py b/manimlib/scene/scene_from_video.py
deleted file mode 100644
index d7957ae1..00000000
--- a/manimlib/scene/scene_from_video.py
+++ /dev/null
@@ -1,53 +0,0 @@
-from tqdm import tqdm as show_progress
-import cv2
-
-from manimlib.scene.scene import Scene
-
-
-# TODO, is this depricated?
-class SceneFromVideo(Scene):
-    def construct(self, file_name,
-                  freeze_last_frame=True,
-                  time_range=None):
-        cap = cv2.VideoCapture(file_name)
-        self.shape = (
-            int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)),
-            int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH))
-        )
-        fps = cap.get(cv2.cv.CV_CAP_PROP_FPS)
-        self.camera.frame_rate = fps
-        frame_count = int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))
-        if time_range is None:
-            start_frame = 0
-            end_frame = frame_count
-        else:
-            start_frame, end_frame = [fps * t for t in time_range]
-
-        frame_count = end_frame - start_frame
-        print("Reading in " + file_name + "...")
-        for count in show_progress(list(range(start_frame, end_frame + 1))):
-            returned, frame = cap.read()
-            if not returned:
-                break
-            # b, g, r = cv2.split(frame)
-            # self.frames.append(cv2.merge([r, g, b]))
-            self.frames.append(frame)
-        cap.release()
-
-        if freeze_last_frame and len(self.frames) > 0:
-            self.original_background = self.background = self.frames[-1]
-
-    def apply_gaussian_blur(self, ksize=(5, 5), sigmaX=5):
-        self.frames = [
-            cv2.GaussianBlur(frame, ksize, sigmaX)
-            for frame in self.frames
-        ]
-
-    def apply_edge_detection(self, threshold1=50, threshold2=100):
-        edged_frames = [
-            cv2.Canny(frame, threshold1, threshold2)
-            for frame in self.frames
-        ]
-        for index in range(len(self.frames)):
-            for i in range(3):
-                self.frames[index][:, :, i] = edged_frames[index]