Merge branch 'fix_pts' into samplers_hack

Author: NicolasHug

src/torchcodec/decoders/_core/VideoDecoder.cpp

@@ -1119,21 +1119,16 @@ VideoDecoder::BatchDecodedOutput VideoDecoder::getFramesDisplayedByTimestamps(
 
     auto it = std::lower_bound(
         stream.allFrames.begin(),
-        stream.allFrames.end(),
+        // See https://github.com/pytorch/torchcodec/pull/286 for why the `- 1`
+        // is needed.
+        stream.allFrames.end() - 1,
         framePts,
         [&stream](const FrameInfo& info, double framePts) {
           return ptsToSeconds(info.nextPts, stream.timeBase) <= framePts;
         });
     int64_t frameIndex = it - stream.allFrames.begin();
-    // If the frame index is larger than the size of allFrames, that means we
-    // couldn't match the pts value to the pts value of a NEXT FRAME. And
-    // that means that this timestamp falls during the time between when the
-    // last frame is displayed, and the video ends. Hence, it should map to the
-    // index of the last frame.
-    frameIndex = std::min(frameIndex, (int64_t)stream.allFrames.size() - 1);
     frameIndices[i] = frameIndex;
   }
-
   return getFramesAtIndices(streamIndex, frameIndices);
 }
 

test/decoders/test_video_decoder_ops.py

@@ -186,6 +186,52 @@ def test_get_frames_by_pts(self):
         with pytest.raises(AssertionError):
             assert_tensor_equal(frames[0], frames[-1])
 
+    def test_pts_apis_against_index_ref(self):
+        # Non-regression test for https://github.com/pytorch/torchcodec/pull/286
+        # Get all frames in the video, then query all frames with all time-based
+        # APIs exactly where those frames are supposed to start. We assert that
+        # we get the expected frame.
+        decoder = create_from_file(str(NASA_VIDEO.path))
+        scan_all_streams_to_update_metadata(decoder)
+        add_video_stream(decoder)
+
+        metadata = get_json_metadata(decoder)
+        metadata_dict = json.loads(metadata)
+        num_frames = metadata_dict["numFrames"]
+        assert num_frames == 390
+
+        stream_index = 3
+        _, all_pts_seconds_ref, _ = zip(
+            *[
+                get_frame_at_index(
+                    decoder, stream_index=stream_index, frame_index=frame_index
+                )
+                for frame_index in range(num_frames)
+            ]
+        )
+        all_pts_seconds_ref = torch.tensor(all_pts_seconds_ref)
+
+        assert len(all_pts_seconds_ref.unique() == len(all_pts_seconds_ref))
+
+        _, pts_seconds, _ = zip(
+            *[get_frame_at_pts(decoder, seconds=pts) for pts in all_pts_seconds_ref]
+        )
+        pts_seconds = torch.tensor(pts_seconds)
+        assert_tensor_equal(pts_seconds, all_pts_seconds_ref)
+
+        _, pts_seconds, _ = get_frames_by_pts_in_range(
+            decoder,
+            stream_index=stream_index,
+            start_seconds=0,
+            stop_seconds=all_pts_seconds_ref[-1] + 1e-4,
+        )
+        assert_tensor_equal(pts_seconds, all_pts_seconds_ref)
+
+        _, pts_seconds, _ = get_frames_by_pts(
+            decoder, stream_index=stream_index, timestamps=all_pts_seconds_ref.tolist()
+        )
+        assert_tensor_equal(pts_seconds, all_pts_seconds_ref)
+
     def test_get_frames_in_range(self):
         decoder = create_from_file(str(NASA_VIDEO.path))
         scan_all_streams_to_update_metadata(decoder)