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* tools/target_dec_fuzzer: Adjust threshold for interplayacmMichael Niedermayer2021-02-04
| | | | | | | | Fixes: Timeout (long -> 1sec) Fixes: 27439/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_INTERPLAY_ACM_fuzzer-5145715814432768 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: use non-obsolete decoding APIAnton Khirnov2021-01-26
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* tools/target_dem_fuzzer.c: Decrease maxblocksMichael Niedermayer2021-01-05
| | | | | | | | | | | | Fixes: Timeout Fixes: 28606/clusterfuzz-testcase-minimized-ffmpeg_dem_FRM_fuzzer-5123311424110592 Fixes: 28796/clusterfuzz-testcase-minimized-ffmpeg_dem_R3D_fuzzer-5945803411685376 Fixes: 28821/clusterfuzz-testcase-minimized-ffmpeg_dem_BRSTM_fuzzer-6044239834251264 Fixes: 28841/clusterfuzz-testcase-minimized-ffmpeg_dem_SIFF_fuzzer-5485368388485120 Fixes: 28862/clusterfuzz-testcase-minimized-ffmpeg_dem_AST_fuzzer-5081306790756352 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 maxpixels for G2MMichael Niedermayer2020-12-24
| | | | | | | | Fixes: Timeout (50sec -> 3sec) Fixes: 27383/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_G2M_fuzzer-5196953666977792 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: remove unused labelMichael Niedermayer2020-12-19
| | | | Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_bsf_fuzzer: set bitstream filter optionsJames Almer2020-11-20
| | | | | | Should increase coverage with some bitstream filters Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_bsf_fuzzer: Call av_bsf_flush() in a fuzzer choosen patternJames Almer2020-11-20
| | | | | | | | This should increase coverage. Based on a commit by Michael Niedermayer Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_dec_fuzzer: Call avcodec_flush_buffers() in a fuzzer choosen ↵Michael Niedermayer2020-11-20
| | | | | | | | | pattern This should increase coverage Signed-off-by: Michael Niedermayer <michael@niedermayer.cc> Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_dem_fuzzer: use avio_context_free() to free the fuzzer's ↵James Almer2020-11-20
| | | | | | | | AVIOContext The doxy for avio_alloc_context() states it must be used for this. Signed-off-by: James Almer <jamrial@gmail.com>
* tools/enum_options: fix build and add to MakefileAnton Khirnov2020-11-20
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* tools/target_dem_fuzzer: Consider it an EIO when reading position wraps ↵Michael Niedermayer2020-11-07
| | | | | | | | | | | | 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>
* tools/target_dec_fuzzer: adjust threshold for wmalosslessMichael Niedermayer2020-10-25
| | | | | | | | 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>
* tools/target_dem_fuzzer: Limit max blocksMichael Niedermayer2020-10-24
| | | | | | | | | | | | | | | | 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>
* tools/target_dec_fuzzer: Adjust threshold for opusMichael Niedermayer2020-10-23
| | | | | | | | 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>
* tools/target_dec_fuzzer: remove calls to avcodec_register*()James Almer2020-10-19
| | | | | | They are no longer needed. Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_dem_fuzzer: switch to the iterate APIJames Almer2020-10-19
| | | | Signed-off-by: James Almer <jamrial@gmail.com>
* tools/target_dec_fuzzer: assume that discarded audio packets produced max ↵Michael Niedermayer2020-10-18
| | | | | | | | | | 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>
* tools/target_dec_fuzzer: Correct maxsamples_per_frame if maxsamples has been ↵Michael Niedermayer2020-10-18
| | | | | | changed Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* tools/target_dem_fuzzer: Set format independent of cMichael Niedermayer2020-10-16
| | | | Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* Add support for building fuzzer tools for an individual demuxerMichael Niedermayer2020-10-12
| | | | Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
* dnn/native: add native support for denseMingyu Yin2020-09-29
| | | | Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
* tools/target_dec_fuzzer: Adjust VQA thresholdMichael Niedermayer2020-09-19
| | | | | | | | 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>
* tools:target_dem_fuzzer: Split into a fuzzer fuzzing at the protocol level ↵Michael Niedermayer2020-09-13
| | | | | | | | 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>
* tools/target_dec_fuzzer: Adjust threshold for WMV3IMAGEMichael Niedermayer2020-09-07
| | | | | | | | 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>
* dnn_backend_native_layer_mathbinary: add floormod supportMingyu Yin2020-08-24
| | | | Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
* tools/target_dec_fuzzer: Adjust threshold for DSTMichael Niedermayer2020-08-18
| | | | | | | | | 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>
* dnn_backend_native_layer_mathunary: add round supportMingyu Yin2020-08-12
| | | | | Signed-off-by: Mingyu Yin <mingyu.yin@intel.com> Reviewed-by: Guo, Yejun <yejun.guo@intel.com>
* tools/target_dec_fuzzer: Adjust threshold for AGMMichael Niedermayer2020-08-11
| | | | | | | | 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>
* dnn/native: add native support for avg_poolTing Fu2020-08-10
| | | | | | | 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>
* dnn_backend_native_layer_mathunary: add floor supportMingyu Yin2020-08-07
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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>
* dnn_backend_native_layer_mathunary: add ceil supportMingyu Yin2020-08-04
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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>
* 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>
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-11 11:03:39 +0000