FFmpeg

Commit Graph

Author	SHA1	Message	Date
James Almer	c055a476b2	tools/target_bsf_fuzzer: set bitstream filter options Should increase coverage with some bitstream filters Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
James Almer	837eb320b8	tools/target_bsf_fuzzer: Call av_bsf_flush() in a fuzzer choosen pattern This should increase coverage. Based on a commit by Michael Niedermayer Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
Michael Niedermayer	cb59cd3466	tools/target_dec_fuzzer: Call avcodec_flush_buffers() in a fuzzer choosen pattern This should increase coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc> Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
James Almer	40dfb4328d	tools/target_dem_fuzzer: use avio_context_free() to free the fuzzer's AVIOContext The doxy for avio_alloc_context() states it must be used for this. Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
Anton Khirnov	65c4d5d72e	tools/enum_options: fix build and add to Makefile	4 years ago
Michael Niedermayer	8fbcc546b8	tools/target_dem_fuzzer: Consider it an EIO when reading position wraps around 64bit Fixes: signed integer overflow: 9223372036854775807 + 564 cannot be represented in type 'long' Fixes: 26494/clusterfuzz-testcase-minimized-ffmpeg_dem_VOC_fuzzer-576754158849228 Fixes: 26549/clusterfuzz-testcase-minimized-ffmpeg_dem_AVS_fuzzer-4844306424397824 FIxes: 26875/clusterfuzz-testcase-minimized-ffmpeg_dem_C93_fuzzer-5996226782429184 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	0d395767ec	tools/target_dec_fuzzer: adjust threshold for wmalossless Fixes: Timeout (>30sec -> 0.5sec) Fixes: 26351/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_WMALOSSLESS_fuzzer-5191487740182528 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	6e64d89410	tools/target_dem_fuzzer: Limit max blocks With a IO block size of 1 byte potentially megabytes are quite slow to read, thus limit the number Fixes: 26511/clusterfuzz-testcase-minimized-ffmpeg_dem_NUV_fuzzer-5679249073373184 Fixes: 26517/clusterfuzz-testcase-minimized-ffmpeg_dem_XMV_fuzzer-6316634501021696 Fixes: 26518/clusterfuzz-testcase-minimized-ffmpeg_dem_WSVQA_fuzzer-485568285324083 Fixes: 26525/clusterfuzz-testcase-minimized-ffmpeg_dem_MSNWC_TCP_fuzzer-5121987011411968 Fixes: 26538/clusterfuzz-testcase-minimized-ffmpeg_dem_DHAV_fuzzer-5441800598454272 Fixes: OOM Fixes: Timeout Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	c5b8f2321c	tools/target_dec_fuzzer: Adjust threshold for opus Fixes: Timeout (12sec -> 3sec) Fixes: 24549/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_LIBOPUS_fuzzer-6211170349088768 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
James Almer	3e4214109a	tools/target_dec_fuzzer: remove calls to avcodec_register*() They are no longer needed. Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
James Almer	a8a1a58af3	tools/target_dem_fuzzer: switch to the iterate API Signed-off-by: James Almer <jamrial@gmail.com>	4 years ago
Michael Niedermayer	c0c6b68ddb	tools/target_dec_fuzzer: assume that discarded audio packets produced max samples We do not know how many samples these produce as its not exported. Alternatively we could export that but as long as its not we better assume its more than 0 as otherwise the thresholds would not work Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	c062dd74d7	tools/target_dec_fuzzer: Correct maxsamples_per_frame if maxsamples has been changed Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	af701196ec	tools/target_dem_fuzzer: Set format independent of c Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	d40679d89c	Add support for building fuzzer tools for an individual demuxer Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Mingyu Yin	ad2546e3b3	dnn/native: add native support for dense Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>	4 years ago
Michael Niedermayer	5dae33bb39	tools/target_dec_fuzzer: Adjust VQA threshold Fixes: Timeout (169sec -> 9sec) Fixes: 23745/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_VQA_fuzzer-5638172179693568 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	e3af2a0756	tools:target_dem_fuzzer: Split into a fuzzer fuzzing at the protocol level and one fuzzing a fixed demuxer input This should improve coverage and should improve the efficiency of seed files Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Michael Niedermayer	a12864938d	tools/target_dec_fuzzer: Adjust threshold for WMV3IMAGE Fixes: Timeout (1131sec -> 1sec) Fixes: 24727/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_WMV3IMAGE_fuzzer-5754167793287168 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Mingyu Yin	3477feb643	dnn_backend_native_layer_mathbinary: add floormod support Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>	4 years ago
Michael Niedermayer	d08c3f56ec	tools/target_dec_fuzzer: Adjust threshold for DST Fixes: Timeout (too long -> 3sec) Fixes: 24239/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_DST_fuzzer-5189061015502848 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>	4 years ago
Mingyu Yin	4ed6bca4ae	dnn_backend_native_layer_mathunary: add round support Signed-off-by: Mingyu Yin <mingyu.yin@intel.com> Reviewed-by: Guo, Yejun <yejun.guo@intel.com>	4 years ago
Michael Niedermayer	4b7189848f	tools/target_dec_fuzzer: Adjust threshold for AGM Fixes: Timeout (142sec -> 2sec) Fixes: 24426/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_AGM_fuzzer-5639724379930624 Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	4 years ago
Ting Fu	91efc41a69	dnn/native: add native support for avg_pool Not support pooling strides in channel dimension yet. Signed-off-by: Ting Fu <ting.fu@intel.com> Reviewed-by: Guo, Yejun <yejun.guo@intel.com>	4 years ago
Mingyu Yin	fab00b0ae0	dnn_backend_native_layer_mathunary: add floor support It can be tested with the model generated with below python script: import tensorflow as tf import os import numpy as np import imageio from tensorflow.python.framework import graph_util name = 'floor' pb_file_path = os.getcwd() if not os.path.exists(pb_file_path+'/{}_savemodel/'.format(name)): os.mkdir(pb_file_path+'/{}_savemodel/'.format(name)) with tf.Session(graph=tf.Graph()) as sess: in_img = imageio.imread('detection.jpg') in_img = in_img.astype(np.float32) in_data = in_img[np.newaxis, :] input_x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in') y_ = tf.math.floor(input_x*255)/255 y = tf.identity(y_, name='dnn_out') sess.run(tf.global_variables_initializer()) constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out']) with tf.gfile.FastGFile(pb_file_path+'/{}_savemodel/model.pb'.format(name), mode='wb') as f: f.write(constant_graph.SerializeToString()) print("model.pb generated, please in ffmpeg path use\n \n \ python tools/python/convert.py {}_savemodel/model.pb --outdir={}_savemodel/ \n \nto generate model.model\n".format(name,name)) output = sess.run(y, feed_dict={ input_x: in_data}) imageio.imsave("out.jpg", np.squeeze(output)) print("To verify, please ffmpeg path use\n \n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow -f framemd5 {}_savemodel/tensorflow_out.md5\n \ or\n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow {}_savemodel/out_tensorflow.jpg\n \nto generate output result of tensorflow model\n".format(name, name, name, name)) print("To verify, please ffmpeg path use\n \n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native -f framemd5 {}_savemodel/native_out.md5\n \ or \n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native {}_savemodel/out_native.jpg\n \nto generate output result of native model\n".format(name, name, name, name)) Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>	4 years ago
Mingyu Yin	9fbdd5454b	dnn_backend_native_layer_mathunary: add ceil support It can be tested with the model generated with below python script: import tensorflow as tf import os import numpy as np import imageio from tensorflow.python.framework import graph_util name = 'ceil' pb_file_path = os.getcwd() if not os.path.exists(pb_file_path+'/{}_savemodel/'.format(name)): os.mkdir(pb_file_path+'/{}_savemodel/'.format(name)) with tf.Session(graph=tf.Graph()) as sess: in_img = imageio.imread('detection.jpg') in_img = in_img.astype(np.float32) in_data = in_img[np.newaxis, :] input_x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in') y = tf.math.ceil( input_x, name='dnn_out') sess.run(tf.global_variables_initializer()) constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out']) with tf.gfile.FastGFile(pb_file_path+'/{}_savemodel/model.pb'.format(name), mode='wb') as f: f.write(constant_graph.SerializeToString()) print("model.pb generated, please in ffmpeg path use\n \n \ python tools/python/convert.py ceil_savemodel/model.pb --outdir=ceil_savemodel/ \n \n \ to generate model.model\n") output = sess.run(y, feed_dict={ input_x: in_data}) imageio.imsave("out.jpg", np.squeeze(output)) print("To verify, please ffmpeg path use\n \n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model=ceil_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow -f framemd5 ceil_savemodel/tensorflow_out.md5\n \n \ to generate output result of tensorflow model\n") print("To verify, please ffmpeg path use\n \n \ ./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model=ceil_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native -f framemd5 ceil_savemodel/native_out.md5\n \n \ to generate output result of native model\n") Signed-off-by: Mingyu Yin <mingyu.yin@intel.com> Reviewed-by: Guo, Yejun <yejun.guo@intel.com>	4 years ago
Ting Fu	c0cdeea0ee	dnn_backend_native_layer_mathunary: add atanh support 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>	5 years ago
Ting Fu	cd2e3a864d	dnn_backend_native_layer_mathunary: add acosh support Signed-off-by: Ting Fu <ting.fu@intel.com>	5 years ago
Ting Fu	9d14b38d9d	dnn_backend_native_layer_mathunary: add asinh support Signed-off-by: Ting Fu <ting.fu@intel.com>	5 years ago
Ting Fu	ea71e731f4	dnn_backend_native_layer_mathunary: add tanh support Signed-off-by: Ting Fu <ting.fu@intel.com>	5 years ago
Ting Fu	62fc7e3035	dnn_backend_native_layer_mathunary: add cosh support Signed-off-by: Ting Fu <ting.fu@intel.com>	5 years ago
Ting Fu	91b4037101	dnn_backend_native_layer_mathunary: add sinh support Signed-off-by: Ting Fu <ting.fu@intel.com>	5 years ago
Ting Fu	13f5613e68	dnn_backend_native_layer_mathunary: add atan support 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>	5 years ago
Ting Fu	461485feac	dnn_backend_native_layer_mathunary: add acos support 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>	5 years ago
Ting Fu	486c0c419d	dnn_backend_native_layer_mathunary: add asin support 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>	5 years ago
Michael Niedermayer	0b182ff66d	tools/target_dec_fuzzer: Adjust threshold for lagarith 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>	5 years ago
Michael Niedermayer	d3747f4431	tools/target_dem_fuzzer: Use file extensions listed in input formats 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>	5 years ago
Ting Fu	22d0860c13	dnn_backend_native_layer_mathunary: add tan support 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>	5 years ago
Ting Fu	88fb494f42	dnn_backend_native_layer_mathunary: add cos support 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>	5 years ago
Ting Fu	0b6d3f0d83	dnn_backend_native_layer_mathunary: add sin support 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>	5 years ago
Michael Niedermayer	3371d0611f	tools/target_dec_fuzzer: enable mjpeg for tiff or tdsc This is needed for fuzzing tiff/tdsc and should increase coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	5 years ago
Michael Niedermayer	3e651eeac4	tools/target_dem_fuzzer: Implement AVSEEK_SIZE Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>	5 years ago
Ting Fu	f73cc61bf5	dnn_backend_native_layer_mathunary: add abs support 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>	5 years ago
Michael Niedermayer	6d4fdb4f5a	tools/target_dec_fuzzer: Adjust max_pixels for AV_CODEC_ID_HAP 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>	5 years ago
Michael Niedermayer	d6824ef905	tools/target_dec_fuzzer: Reduce maxpixels for HEVC 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>	5 years ago
Michael Niedermayer	05d364dccc	tools/target_dec_fuzzer: Do not test AV_CODEC_FLAG2_FAST with AV_CODEC_ID_H264 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>	5 years ago
Anton Khirnov	ea980d4162	fate: add tests for h264 and vp9 video enc parameters export	5 years ago
Anton Khirnov	bf80725352	lavc: rename bsf.h to bsf_internal.h This will allow adding a public header named bsf.h	5 years ago
Michael Niedermayer	4f54982773	tools/target_dec_fuzzer: Adjust threshold for PNG and APNG 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>	5 years ago
Guo, Yejun	71e28c5422	dnn/native: add native support for minimum 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>	5 years ago

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597 Commits (bcdf67c7fa49fec946cd681d1a5b46d5bde6f562)