With the Kaluga devkit, the camera interferes with the JTAG function.
However, having DEBUG turned on e.g., to get extended debug information
on the UART debug connection remains useful.
Now, by arranging to add to CFLAGS += -DDEBUG -DENABLE_JTAG=0, this
configuration is easy to achieve.
It's intended that the actual timeout always be at least the requested
timeout. However, due to multiplying by the wrong factor to get from
seconds to cycles, a timeout request of e.g., 8.1s (which is less than
8.192s) would give an actual timeout of 8, not 16 as it should.
By having a pair of buffers, the capture hardware can fill one buffer while
Python code (including displayio, etc) operates on the other buffer. This
increases the responsiveness of camera-using code.
On the Kaluga it makes the following improvements:
* 320x240 viewfinder at 30fps instead of 15fps using directio
* 240x240 animated gif capture at 10fps instead of 7.5fps
As discussed at length on Discord, the "usual end user" code will look like
this:
camera = ...
with camera.continuous_capture(buffer1, buffer2) as capture:
for frame in capture:
# Do something with frame
However, rather than presenting a context manager, the core code consists of
three new functions to start & stop continuous capture, and to get the next
frame. The reason is twofold. First, it's simply easier to implement the
context manager object in pure Python. Second, for more advanced usage, the
context manager may be too limiting, and it's easier to iterate on the right
design in Python code. In particular, I noticed that adapting the
JPEG-capturing programs to use continuous capture mode needed a change in
program structure.
The camera app was structured as
```python
while True:
if shutter button was just pressed:
capture a jpeg frame
else:
update the viewfinder
```
However, "capture a jpeg frame" needs to (A) switch the camera settings and (B)
capture into a different, larger buffer then (C) return to the earlier
settings. This can't be done during continuous capture mode. So just
restructuring it as follows isn't going to work:
```python
with camera.continuous_capture(buffer1, buffer2) as capture:
for frame in capture:
if shutter button was just pressed:
capture a jpeg frame, without disturbing continuous capture mode
else:
update the viewfinder
```
The continuous mode is only implemented in the espressif port; others
will throw an exception if the associated methods are invoked. It's not
impossible to implement there, just not a priority, since these micros don't
have enough RAM for two framebuffer copies at any resonable sizes.
The capture code, including single-shot capture, now take mp_obj_t in the
common-hal layer, instead of a buffer & length. This was done for the
continuous capture mode because it has to identify & return to the user the
proper Python object representing the original buffer. In the Espressif port,
it was convenient to implement single capture in terms of a multi-capture,
which is why I changed the singleshot routine's signature too.
This involves:
* Adding a new "L8" colorspace for colorconverters
* factoring out displayio_colorconverter_convert_pixel
* Making a minimal "colorspace only" version of displayio for the
unix port (testing purposes)
* fixing an error message
I only tested writing B&W animated images, with the following script:
```python
import displayio
import gifio
with gifio.GifWriter("foo.gif", 64, 64, displayio.Colorspace.L8) as g:
for i in range(0, 256, 14):
data = bytes([i, 255-i] * 32 + [255-i, i] * 32) * 32
print("add_frame")
g.add_frame(data)
# expected to raise an error, buffer is not big enough
with gifio.GifWriter("/dev/null", 64, 64, displayio.Colorspace.L8) as g:
g.add_frame(bytes([3,3,3]))
```
Jeff Epler
Scott Shawcroft
EmergReanimator
Dan Halbert
lady ada
root
Kong Wai Weng
Scott Shawcroft
Dan Halbert
Jeff Epler
Max Holliday
Pierre Constantineau