Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Fixes: Assertion failure
Fixes: 22737/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_WMALOSSLESS_fuzzer-5958388889681920

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: signed integer overflow: 2147483647 + 1 cannot be represented in type 'int'
Fixes: 22975/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_LOCO_fuzzer-5658160970072064

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: division by zero
Fixes: 23162/clusterfuzz-testcase-minimized-ffmpeg_DEMUXER_fuzzer-4856420817436672

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: signed integer overflow: 9223372036854775807 - -1 cannot be represented in type 'long'
Fixes: 23167/clusterfuzz-testcase-minimized-ffmpeg_DEMUXER_fuzzer-6425051741290496

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: Timeout (85sec -> 0.5sec)
Fixes: 20791/clusterfuzz-testcase-minimized-ffmpeg_BSF_AV1_FRAME_SPLIT_fuzzer-5659537719951360
Fixes: 21214/clusterfuzz-testcase-minimized-ffmpeg_BSF_MPEG2_METADATA_fuzzer-5165560875974656
Fixes: 21247/clusterfuzz-testcase-minimized-ffmpeg_BSF_H264_METADATA_fuzzer-5715175257931776

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Signed-off-by: Dale Curtis <dalecurtis@chromium.org>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Signed-off-by: Fei Wang <fei.w.wang@intel.com>

Signed-off-by: Fei Wang <fei.w.wang@intel.com>

The format is packed RGB with each channel 10 bits available and
include 2 bits unused.

Signed-off-by: Fei Wang <fei.w.wang@intel.com>

Fixes: Timeout (3minute 49 sec -> 3sec)
Fixes: 22020/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_LAGARITH_fuzzer-5708544679870464

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Found-by: Kieran
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: integer overflow
Fixes: 22285/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_SNOW_fuzzer-5682428762128384

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Fixes: left shift of 243 by 24 places cannot be represented in type 'int'
Fixes: 22716/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_MOVTEXT_fuzzer-5704263425851392

Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

This should make it easier for the fuzzer to fuzz formats being detected only by
file extension and thus increase coverage

Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>

Signed-off-by: Limin Wang <lance.lmwang@gmail.com>

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

It can be tested with the model generated with below python scripy

import tensorflow as tf
import numpy as np
import imageio

in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]

x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 0.78)
x2 = tf.tan(x1)
y = tf.identity(x2, name='dnn_out')

sess=tf.Session()
sess.run(tf.global_variables_initializer())

graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)

print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")

output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

It can be tested with the model generated with below python scripy

import tensorflow as tf
import numpy as np
import imageio

in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]

x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 1.5)
x2 = tf.cos(x1)
y = tf.identity(x2, name='dnn_out')

sess=tf.Session()
sess.run(tf.global_variables_initializer())

graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)

print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")

output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

It can be tested with the model file generated with below python scripy:

import tensorflow as tf
import numpy as np
import imageio

in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]

x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 3.14)
x2 = tf.sin(x1)
y = tf.identity(x2, name='dnn_out')

sess=tf.Session()
sess.run(tf.global_variables_initializer())

graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)

print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")

output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>

Two kinds of errors can happen when working with dynamic buffers:
(Re)allocation errors or truncation errors (one has to truncate the
buffer to a size of INT_MAX because avio_close_dyn_buf() and
avio_get_dyn_buf() both return an int). Right now, avio_get_dyn_buf()
returns an empty buffer in either case. But given that
avio_get_dyn_buf() does not destroy the dynamic buffer, one can return
the buffer in case of truncation and let the user check the error flags
and decide for himself instead of hardcoding a single way to proceed
in case of truncation.

(This actually restores the behaviour from before commit
163bb9ac0af495a5cb95441bdb5c02170440d28c.)

Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>

Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>

This has originally been done in 568e18b15e
as a precaution against integer overflows, but it is actually easy to
support the full range of int without overflows.

Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>

Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>

If adding two ints overflows, it doesn't matter whether the result will
be stored in an unsigned or not; and checking afterwards does not make it
retroactively defined.

Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>