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* dnn_backend_native_layer_mathunary: add atanh supportTing Fu2020-07-06
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It can be tested with the model generated with below python script: 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') please uncomment the part you want to test x_sinh_1 = tf.sinh(x) x_out = tf.divide(x_sinh_1, 1.176) # sinh(1.0) x_cosh_1 = tf.cosh(x) x_out = tf.divide(x_cosh_1, 1.55) # cosh(1.0) x_tanh_1 = tf.tanh(x) x__out = tf.divide(x_tanh_1, 0.77) # tanh(1.0) x_asinh_1 = tf.asinh(x) x_out = tf.divide(x_asinh_1, 0.89) # asinh(1.0/1.1) x_acosh_1 = tf.add(x, 1.1) x_acosh_2 = tf.acosh(x_acosh_1) # accept (1, inf) x_out = tf.divide(x_acosh_2, 1.4) # acosh(2.1) x_atanh_1 = tf.divide(x, 1.1) x_atanh_2 = tf.atanh(x_atanh_1) # accept (-1, 1) x_out = tf.divide(x_atanh_2, 1.55) # atanhh(1.0/1.1) y = tf.identity(x_out, name='dnn_out') #please only preserve the x_out you want to test 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>
* dnn_backend_native_layer_mathunary: add acosh supportTing Fu2020-07-06
| | | | Signed-off-by: Ting Fu <ting.fu@intel.com>
* dnn_backend_native_layer_mathunary: add asinh supportTing Fu2020-07-06
| | | | Signed-off-by: Ting Fu <ting.fu@intel.com>
* dnn_backend_native_layer_mathunary: add tanh supportTing Fu2020-07-06
| | | | Signed-off-by: Ting Fu <ting.fu@intel.com>
* dnn_backend_native_layer_mathunary: add cosh supportTing Fu2020-07-06
| | | | Signed-off-by: Ting Fu <ting.fu@intel.com>
* dnn_backend_native_layer_mathunary: add sinh supportTing Fu2020-07-06
| | | | Signed-off-by: Ting Fu <ting.fu@intel.com>
* dnn_backend_native_layer_mathunary: add atan supportTing Fu2020-06-25
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It can be tested with the model generated with below python script: 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.atan(x) x2 = tf.divide(x1, 3.1416/4) # pi/4 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>
* dnn_backend_native_layer_mathunary: add acos supportTing Fu2020-06-25
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It can be tested with the model generated with below python script: 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.acos(x) x2 = tf.divide(x1, 3.1416/2) # pi/2 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>
* dnn_backend_native_layer_mathunary: add asin supportTing Fu2020-06-25
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It can be tested with the model generated with below python script: 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.asin(x) x2 = tf.divide(x1, 3.1416/2) # pi/2 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>
* tools/target_dec_fuzzer: Adjust threshold for lagarithMichael Niedermayer2020-06-11
| | | | | | | | 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>
* tools/target_dem_fuzzer: Use file extensions listed in input formatsMichael Niedermayer2020-06-11
| | | | | | | 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>
* dnn_backend_native_layer_mathunary: add tan supportTing Fu2020-06-11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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>
* dnn_backend_native_layer_mathunary: add cos supportTing Fu2020-06-11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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>
* dnn_backend_native_layer_mathunary: add sin supportTing Fu2020-06-11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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>
* tools/target_dec_fuzzer: enable mjpeg for tiff or tdscMichael Niedermayer2020-06-08
| | | | | | This is needed for fuzzing tiff/tdsc and should increase coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dem_fuzzer: Implement AVSEEK_SIZEMichael Niedermayer2020-06-08
| | | | Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* dnn_backend_native_layer_mathunary: add abs supportTing Fu2020-05-28
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | more math unary operations will be added here 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.subtract(x, 0.5) x2 = tf.abs(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>
* tools/target_dec_fuzzer: Adjust max_pixels for AV_CODEC_ID_HAPMichael Niedermayer2020-05-27
| | | | | | | | Fixes: Timeout (170sec -> 6sec) Fixes: 20956/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_HAP_fuzzer-5713643025203200 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Reduce maxpixels for HEVCMichael Niedermayer2020-05-27
| | | | | | | | | | | | high resolutions with only small blocks appear to be rather slow with the fuzzer + sanitizers. A solution which makes this run faster is welcome. Fixes: Timeout (did not wait -> 17sec) Fixes: 21006/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_HEVC_fuzzer-6002552539971584 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Do not test AV_CODEC_FLAG2_FAST with AV_CODEC_ID_H264Michael Niedermayer2020-05-27
| | | | | | | | | This combination skips allocating large padding which can read out of array Fixes: 20978/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_H264_fuzzer-5746381832847360 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* fate: add tests for h264 and vp9 video enc parameters exportAnton Khirnov2020-05-25
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* lavc: rename bsf.h to bsf_internal.hAnton Khirnov2020-05-22
| | | | This will allow adding a public header named bsf.h
* tools/target_dec_fuzzer: Adjust threshold for PNG and APNGMichael Niedermayer2020-05-10
| | | | | | | | Fixes: Timeout (84sec -> 2sec) Fixes: 21127/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_APNG_fuzzer-5098412367413248 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* dnn/native: add native support for minimumGuo, Yejun2020-05-08
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | it can be tested with model file generated with below python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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.minimum(0.7, x) x2 = tf.maximum(x1, 0.4) 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: Guo, Yejun <yejun.guo@intel.com>
* tools: fix const specifier for AVInputFormatJosh de Kock2020-04-30
| | | | Signed-off-by: Josh de Kock <josh@itanimul.li>
* dnn/native: add native support for divideGuo, Yejun2020-04-22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | it can be tested with model file generated with below python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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') z1 = 2 / x z2 = 1 / z1 z3 = z2 / 0.25 + 0.3 z4 = z3 - x * 1.5 - 0.3 y = tf.identity(z4, 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: Guo, Yejun <yejun.guo@intel.com>
* dnn/native: add native support for 'mul'Guo, Yejun2020-04-22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | it can be tested with model file generated from above python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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') z1 = 0.5 + 0.3 * x z2 = z1 * 4 z3 = z2 - x - 2.0 y = tf.identity(z3, 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: Guo, Yejun <yejun.guo@intel.com>
* dnn/native: add native support for 'add'Guo, Yejun2020-04-22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | It can be tested with the model file generated with below python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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') z1 = 0.039 + x z2 = x + 0.042 z3 = z1 + z2 z4 = z3 - 0.381 z5 = z4 - x y = tf.math.maximum(z5, 0.0, 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: Guo, Yejun <yejun.guo@intel.com>
* tools: stop using deprecated av_codec_next()Josh de Kock2020-04-20
| | | | Signed-off-by: Josh de Kock <josh@itanimul.li>
* tools/target_dec_fuzzer: Adjust threshold for zerocodecMichael Niedermayer2020-04-12
| | | | | | | | Fixes: Timeout (147sec -> 1sec) Fixes: 20764/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_ZEROCODEC_fuzzer-5068274603917312 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Adjust threshold for screenpressoMichael Niedermayer2020-04-07
| | | | | | | | Fixes: Timeout (332 -> 21 sec) Fixes: 20280/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_SCREENPRESSO_fuzzer-6238663432470528 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* dnn_backend_native_layer_mathbinary: add sub supportGuo, Yejun2020-04-07
| | | | | | more math binary operations will be added here Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
* tools/target_dec_fuzzer: limit per frame samples for APEMichael Niedermayer2020-01-30
| | | | | | | | | | APE in its highest compression mode is really slow so even one frame of millions of samples takes a long time Fixes: Timeout (too long -> 3sec) Fixes: 19937/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_APE_fuzzer-5751668818051072 Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Add threshold for ALSMichael Niedermayer2020-01-30
| | | | | | | | Fixes: Timeout (253sec -> 16sec) Fixes: 18668/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_ALS_fuzzer-6227155369590784 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Add threshold for IFF_ILBMMichael Niedermayer2020-01-29
| | | | | | | | | Fixes: Timeout (32 -> 1sec) Fixes: 20138/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_IFF_ILBM_fuzzer-5634665251864576 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Reviewed-by: Peter Ross <pross@xvid.org> Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Sort threshold list alphabeticallyMichael Niedermayer2020-01-29
| | | | | | | This also removes the comments as they are hard to maintain together with sorted lists Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Use codec_tags listMichael Niedermayer2020-01-22
| | | | | | | This should make it much quicker for the fuzzer to test real relevant codec_tags Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Also Fuzz with CPU optimizations disabledMichael Niedermayer2020-01-21
| | | | | | This should improve coverage of *_c() Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Fuzz private options of AC3/E-AC3Michael Niedermayer2020-01-21
| | | | | | This should improve AC-3 coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Fuzz idct_algo valueMichael Niedermayer2020-01-21
| | | | | | This should improve coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Adjust threshold for RASCMichael Niedermayer2020-01-11
| | | | | | | | Fixes: Timeout(35sec -> 4sec) Fixes: 19289/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_RASC_fuzzer-5676526398078976 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Stop negative block_align and sampling rateMichael Niedermayer2019-12-31
| | | | | | | These are checked for early in avcodec_open2() and do not really test the decoder but instead waste resources which could be better spend fuzzing the actual decoder Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Adjust threshold for dstMichael Niedermayer2019-12-15
| | | | | | | | Fixes: Timeout (400sec -> 14sec) Fixes: 18989/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_DST_fuzzer-5175008116867072 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* convert_from_tensorflow.py: add support when kernel size is 1*1 with one ↵Guo, Yejun2019-12-13
| | | | | | | input/output channel (gray image) Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
* tools/target_dec_fuzzer: Also fuzz request_channel_layoutMichael Niedermayer2019-12-08
| | | | | | This should improve coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools: add a fuzzer tool for bitstream filtersJames Almer2019-12-05
| | | | | Reviewed-by: Michael Niedermayer <michael@niedermayer.cc> Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_dec_fuzzer: Support setting AV_CODEC_FLAG2_FASTMichael Niedermayer2019-12-03
| | | | | | This should improve coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Support fuzzing error detectionMichael Niedermayer2019-12-03
| | | | | | This should increase coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Adjust threshold for VP9Michael Niedermayer2019-11-24
| | | | | | | | | | | | The threshold is chosen so that the worse frames would together not take excessive time. A better solution is welcome! Fixes: Timeout (308sec ->102ms) Fixes: 18314/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_VP9_fuzzer-5701689176227840 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dec_fuzzer: Adjust threshold for smackerMichael Niedermayer2019-11-09
| | | | | | | | Fixes: Timeout (65sec -> 0.5sec) Fixes: 18072/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_SMACKER_fuzzer-5722709366931456 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-04 11:19:05 +0000