Python超人-宇宙模拟器

sim_scenes/solar_system/halley_comet_sim.py

@@ -370,7 +370,7 @@ if __name__ == '__main__':
                cosmic_bg='',
                show_trail=True,
                # bg_music='sounds/no_glory.mp3',
-               # show_camera_info=False,
+               show_camera_info=False,
                save_as_video=True,
                show_control_info=False,
                timer_enabled=True,

simulators/ursina/entities/video_recorder.py

@@ -2,6 +2,7 @@ from ursina import *
 import os, shutil
 import builtins
 import numpy as np
+import cv2
 
 
 class CubeMapVideoRecorder(Entity):
@@ -65,6 +66,13 @@ class VideoRecorder(Entity):
 
         self.max_frames = int(self.duration * self.fps)
         self.frames = []
+        self.save_name = "video_temp.mp4"
+        self.video = self.create_video(864, 1536)
+
+    def create_video(self, height, width):
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        video = cv2.VideoWriter(self.save_name, fourcc, self.fps, (width, height))
+        return video
 
     def start_recording(self):
         print('start recording,', self.duration, self.file_path)
@@ -74,17 +82,35 @@ class VideoRecorder(Entity):
         self.max_frames = self.duration * self.fps
         if not self.file_path.exists():
             self.file_path.mkdir()
-        base.movie(namePrefix=f'\\video_temp\\{self.video_name}', duration=2.0, fps=30, format='png', sd=4)
+        # base.movie(namePrefix=f'\\video_temp\\{self.video_name}', duration=2.0, fps=30, format='png', sd=4)
 
         self.recording = True
-        invoke(self.stop_recording, delay=self.duration)
+        # invoke(self.stop_recording, delay=self.duration)
 
     def stop_recording(self):
         self.recording = False
         window.fps_counter.enabled = True
         window.exit_button.visible = True
         print('stop recording')
-        self.convert_to_gif()
+        self.convert_to_mp4()
+
+    def convert_to_mp4(self):
+        print("视频保存中")
+        self.video.release()
+        cv2.destroyAllWindows()
+        # crop('video.mp4')
+        print("视频保存完成")
+        print(self.save_name)
+
+    def screenshot_to_opencv_img(self, texture):
+        # 将Texture对象转换为numpy数组
+        array = texture.to_array()
+        # 将数组reshape为4D，以便opencv可以正确读取
+        array = np.reshape(array, (texture.height, texture.width, -1))
+        # 转换为opencv读取的格式，注意需要先安装opencv库
+        img = cv2.cvtColor(array,
+                           cv2.COLOR_RGB2BGR)  # 这里的cv2.COLOR_RGB2BGR是将RGB格式转换为BGR格式，因为Ursina使用的是RGB格式，而opencv使用的是BGR格式
+        return img
 
     def update(self):
         if not self.recording:
@@ -92,22 +118,49 @@ class VideoRecorder(Entity):
 
         self.t += time.dt
         if self.t >= 1 / 30:
-                base.screenshot(
-                    namePrefix='\\video_temp\\' + self.video_name + '_' + str(self.i).zfill(4) + '.png',
-                    defaultFilename=0,
-                )
+            # base.screenshot(
+            #     namePrefix='\\video_temp\\' + self.video_name + '_' + str(self.i).zfill(4) + '.png',
+            #     defaultFilename=0,
+            # )
             self.t = 0
-        # # self.frames.append(self.renderToPNM())
-        # image = base.win.getScreenshot()
-        # data = image.getRamImageAs("RGB").getData()
-        # # from PIL import Image
-        # # image = Image.fromarray(data)
-        # # img = data.convert("RGBA")
-        # data = np.array(data)
+        # image = deepcopy(camera.render_texture)
+        # self.frames.append(self.renderToPNM())
+        from PIL import Image
+        import io
+        import imageio
+        image = base.win.getScreenshot()
+        # image = image.get_internal_image()
+
+        data = image.getRamImageAs("BGR").getData()
+        np_data = np.frombuffer(data, dtype=np.uint8)
         #
+        img_data = np.reshape(np_data, (864, 1536, 3))
+        # img = Image.fromarray(img_data)
+        # img = self.screenshot_to_opencv_img(image)
+        # img = np.array(data)
+        # image = Image.open(io.BytesIO(data))
+        # image = Image.fromarray(np.array(data))
+        # img = data.convert("RGBA")
+        # data = np.array(data)
+        # 获取图片的宽和高
+        width = img_data.shape[1]
+        height = img_data.shape[0]
+
+        # 创建一个空的数组，用于存储还原后的图像
+        normal_image = np.zeros((height, width, 3), dtype=np.uint8)
+
+        # 将颠倒图像的像素还原到正常图像中
+        for i in range(height):
+            for j in range(width):
+                normal_image[i, j] = img_data[height - i - 1, j]
+
         # # image = deepcopy(camera.render_texture)
         # self.frames.append(data)
         self.i += 1
+        # img_bgr = cv2.cvtColor(img, cv2.COLOR_RGBA2BGR)
+        # if imageNum < self.fps * args.total_time:
+        # show_image(frame)
+        self.video.write(normal_image)
 
     # store screenshot in memory
     # def renderToPNM(self):