ggerganov · ggerganov · Oct 30, 2023 · Oct 11, 2023 · Oct 11, 2023 · Oct 11, 2023
diff --git a/README.md b/README.md
@@ -47,6 +47,7 @@ Some of the development is currently happening in the [llama.cpp](https://github
 - [X] Example of ChatGLM inference [li-plus/chatglm.cpp](https://github.com/li-plus/chatglm.cpp)
 - [X] Example of Stable Diffusion inference [leejet/stable-diffusion.cpp](https://github.com/leejet/stable-diffusion.cpp)
 - [X] Example of Qwen inference [QwenLM/qwen.cpp](https://github.com/QwenLM/qwen.cpp)
+- [X] Example of YOLO inference [examples/yolo](https://github.com/ggerganov/ggml/tree/master/examples/yolo)
 
 ## Whisper inference (example)
 

diff --git a/ci/run.sh b/ci/run.sh
@@ -264,6 +264,43 @@ function gg_sum_sam {
     gg_printf '```\n'
 }
 
+# yolo
+
+function gg_run_yolo {
+    cd ${SRC}
+
+    gg_wget models-mnt/yolo/ https://pjreddie.com/media/files/yolov3-tiny.weights
+    gg_wget models-mnt/yolo/ https://raw.githubusercontent.com/pjreddie/darknet/master/data/dog.jpg
+
+    cd build-ci-release
+    cp -r ../examples/yolo/data .
+
+    set -e
+
+    path_models="../models-mnt/yolo/"
+
+    python3 ../examples/yolo/convert-yolov3-tiny.py ${path_models}/yolov3-tiny.weights
+
+    (time ./bin/yolov3-tiny -m yolov3-tiny.gguf -i ${path_models}/dog.jpg ) 2>&1 | tee -a $OUT/${ci}-main.log
+
+    grep -q "dog: 57%" $OUT/${ci}-main.log
+    grep -q "car: 52%" $OUT/${ci}-main.log
+    grep -q "truck: 56%" $OUT/${ci}-main.log
+    grep -q "bicycle: 59%" $OUT/${ci}-main.log
+
+    set +e
+}
+
+function gg_sum_yolo {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Run YOLO\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-main.log)"
+    gg_printf '```\n'
+}
+
 # mpt
 
 function gg_run_mpt {
@@ -324,6 +361,7 @@ test $ret -eq 0 && gg_run gpt_2
 test $ret -eq 0 && gg_run mnist
 test $ret -eq 0 && gg_run whisper
 test $ret -eq 0 && gg_run sam
+test $ret -eq 0 && gg_run yolo
 
 if [ -z $GG_BUILD_LOW_PERF ]; then
     if [ -z ${GG_BUILD_VRAM_GB} ] || [ ${GG_BUILD_VRAM_GB} -ge 16 ]; then

diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
@@ -28,3 +28,4 @@ add_subdirectory(replit)
 add_subdirectory(mpt)
 add_subdirectory(starcoder)
 add_subdirectory(sam)
+add_subdirectory(yolo)
diff --git a/examples/yolo/CMakeLists.txt b/examples/yolo/CMakeLists.txt
@@ -0,0 +1,6 @@
+#
+# yolov3-tiny
+
+set(TEST_TARGET yolov3-tiny)
+add_executable(${TEST_TARGET} yolov3-tiny.cpp yolo-image.cpp)
+target_link_libraries(${TEST_TARGET} PRIVATE ggml common)
diff --git a/examples/yolo/README.md b/examples/yolo/README.md
@@ -0,0 +1,52 @@
+This example shows how to implement YOLO object detection with ggml using pretrained model.
+
+# YOLOv3-tiny
+
+Download the model weights:
+
+```bash
+$ wget https://pjreddie.com/media/files/yolov3-tiny.weights
+$ sha1sum yolov3-tiny.weights 
+40f3c11883bef62fd850213bc14266632ed4414f  yolov3-tiny.weights
+```
+
+Convert the weights to GGUF format:
+
+```bash
+$ ./convert-yolov3-tiny.py yolov3-tiny.weights
+yolov3-tiny.weights converted to yolov3-tiny.gguf
+```
+
+Object detection:
+
+```bash
+$ wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/dog.jpg
+$ ./yolov3-tiny -m yolov3-tiny.gguf -i dog.jpg
+Layer  0 output shape:  416 x 416 x   16 x   1
+Layer  1 output shape:  208 x 208 x   16 x   1
+Layer  2 output shape:  208 x 208 x   32 x   1
+Layer  3 output shape:  104 x 104 x   32 x   1
+Layer  4 output shape:  104 x 104 x   64 x   1
+Layer  5 output shape:   52 x  52 x   64 x   1
+Layer  6 output shape:   52 x  52 x  128 x   1
+Layer  7 output shape:   26 x  26 x  128 x   1
+Layer  8 output shape:   26 x  26 x  256 x   1
+Layer  9 output shape:   13 x  13 x  256 x   1
+Layer 10 output shape:   13 x  13 x  512 x   1
+Layer 11 output shape:   13 x  13 x  512 x   1
+Layer 12 output shape:   13 x  13 x 1024 x   1
+Layer 13 output shape:   13 x  13 x  256 x   1
+Layer 14 output shape:   13 x  13 x  512 x   1
+Layer 15 output shape:   13 x  13 x  255 x   1
+Layer 18 output shape:   13 x  13 x  128 x   1
+Layer 19 output shape:   26 x  26 x  128 x   1
+Layer 20 output shape:   26 x  26 x  384 x   1
+Layer 21 output shape:   26 x  26 x  256 x   1
+Layer 22 output shape:   26 x  26 x  255 x   1
+dog: 57%
+car: 52%
+truck: 56%
+car: 62%
+bicycle: 59%
+Detected objects saved in 'predictions.jpg' (time: 0.357000 sec.)
+```
diff --git a/examples/yolo/convert-yolov3-tiny.py b/examples/yolo/convert-yolov3-tiny.py
@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+import sys
+import gguf
+import numpy as np
+
+def save_conv2d_layer(f, gguf_writer, prefix, inp_c, filters, size, batch_normalize=True):
+    biases = np.fromfile(f, dtype=np.float32, count=filters)
+    gguf_writer.add_tensor(prefix + "_biases", biases, raw_shape=(1, filters, 1, 1))
+
+    if batch_normalize:
+        scales = np.fromfile(f, dtype=np.float32, count=filters)
+        gguf_writer.add_tensor(prefix + "_scales", scales, raw_shape=(1, filters, 1, 1))
+        rolling_mean = np.fromfile(f, dtype=np.float32, count=filters)
+        gguf_writer.add_tensor(prefix + "_rolling_mean", rolling_mean, raw_shape=(1, filters, 1, 1))
+        rolling_variance = np.fromfile(f, dtype=np.float32, count=filters)
+        gguf_writer.add_tensor(prefix + "_rolling_variance", rolling_variance, raw_shape=(1, filters, 1, 1))
+
+    weights_count = filters * inp_c * size * size
+    l0_weights = np.fromfile(f, dtype=np.float32, count=weights_count)
+    ## ggml doesn't support f32 convolution yet, use f16 instead
+    l0_weights = l0_weights.astype(np.float16)
+    gguf_writer.add_tensor(prefix + "_weights", l0_weights, raw_shape=(filters, inp_c, size, size))
+
+
+if __name__ == '__main__':
+    if len(sys.argv) != 2:
+        print("Usage: %s <yolov3-tiny.weights>" % sys.argv[0])
+        sys.exit(1)
+    outfile = 'yolov3-tiny.gguf'
+    gguf_writer = gguf.GGUFWriter(outfile, 'yolov3-tiny')
+
+    f = open(sys.argv[1], 'rb')
+    f.read(20) # skip header
+    save_conv2d_layer(f, gguf_writer, "l0", 3, 16, 3)
+    save_conv2d_layer(f, gguf_writer, "l1", 16, 32, 3)
+    save_conv2d_layer(f, gguf_writer, "l2", 32, 64, 3)
+    save_conv2d_layer(f, gguf_writer, "l3", 64, 128, 3)
+    save_conv2d_layer(f, gguf_writer, "l4", 128, 256, 3)
+    save_conv2d_layer(f, gguf_writer, "l5", 256, 512, 3)
+    save_conv2d_layer(f, gguf_writer, "l6", 512, 1024, 3)
+    save_conv2d_layer(f, gguf_writer, "l7", 1024, 256, 1)
+    save_conv2d_layer(f, gguf_writer, "l8", 256, 512, 3)
+    save_conv2d_layer(f, gguf_writer, "l9", 512, 255, 1, batch_normalize=False)
+    save_conv2d_layer(f, gguf_writer, "l10", 256, 128, 1)
+    save_conv2d_layer(f, gguf_writer, "l11", 384, 256, 3)
+    save_conv2d_layer(f, gguf_writer, "l12", 256, 255, 1, batch_normalize=False)
+    f.close()
+
+    gguf_writer.write_header_to_file()
+    gguf_writer.write_kv_data_to_file()
+    gguf_writer.write_tensors_to_file()
+    gguf_writer.close()
+    print("{} converted to {}".format(sys.argv[1], outfile))
diff --git a/examples/yolo/data/coco.names b/examples/yolo/data/coco.names
@@ -0,0 +1,80 @@
+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
diff --git a/examples/yolo/data/labels/100_0.png b/examples/yolo/data/labels/100_0.png
diff --git a/examples/yolo/data/labels/100_1.png b/examples/yolo/data/labels/100_1.png
diff --git a/examples/yolo/data/labels/100_2.png b/examples/yolo/data/labels/100_2.png
diff --git a/examples/yolo/data/labels/100_3.png b/examples/yolo/data/labels/100_3.png
diff --git a/examples/yolo/data/labels/100_4.png b/examples/yolo/data/labels/100_4.png
diff --git a/examples/yolo/data/labels/100_5.png b/examples/yolo/data/labels/100_5.png
diff --git a/examples/yolo/data/labels/100_6.png b/examples/yolo/data/labels/100_6.png
diff --git a/examples/yolo/data/labels/100_7.png b/examples/yolo/data/labels/100_7.png
diff --git a/examples/yolo/data/labels/101_0.png b/examples/yolo/data/labels/101_0.png
diff --git a/examples/yolo/data/labels/101_1.png b/examples/yolo/data/labels/101_1.png
diff --git a/examples/yolo/data/labels/101_2.png b/examples/yolo/data/labels/101_2.png
diff --git a/examples/yolo/data/labels/101_3.png b/examples/yolo/data/labels/101_3.png
diff --git a/examples/yolo/data/labels/101_4.png b/examples/yolo/data/labels/101_4.png
diff --git a/examples/yolo/data/labels/101_5.png b/examples/yolo/data/labels/101_5.png
diff --git a/examples/yolo/data/labels/101_6.png b/examples/yolo/data/labels/101_6.png
diff --git a/examples/yolo/data/labels/101_7.png b/examples/yolo/data/labels/101_7.png
diff --git a/examples/yolo/data/labels/102_0.png b/examples/yolo/data/labels/102_0.png
diff --git a/examples/yolo/data/labels/102_1.png b/examples/yolo/data/labels/102_1.png
diff --git a/examples/yolo/data/labels/102_2.png b/examples/yolo/data/labels/102_2.png
diff --git a/examples/yolo/data/labels/102_3.png b/examples/yolo/data/labels/102_3.png
diff --git a/examples/yolo/data/labels/102_4.png b/examples/yolo/data/labels/102_4.png
diff --git a/examples/yolo/data/labels/102_5.png b/examples/yolo/data/labels/102_5.png
diff --git a/examples/yolo/data/labels/102_6.png b/examples/yolo/data/labels/102_6.png
diff --git a/examples/yolo/data/labels/102_7.png b/examples/yolo/data/labels/102_7.png
diff --git a/examples/yolo/data/labels/103_0.png b/examples/yolo/data/labels/103_0.png
diff --git a/examples/yolo/data/labels/103_1.png b/examples/yolo/data/labels/103_1.png
diff --git a/examples/yolo/data/labels/103_2.png b/examples/yolo/data/labels/103_2.png
diff --git a/examples/yolo/data/labels/103_3.png b/examples/yolo/data/labels/103_3.png
diff --git a/examples/yolo/data/labels/103_4.png b/examples/yolo/data/labels/103_4.png
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