v1.6.0

Author: MarcA711

.gitignore

@@ -1,2 +1,4 @@
 /input/
-/output/
+/output/
+
+!/input/model_onnx.py

conv.py

@@ -1,63 +1,72 @@
 from rknn.api import RKNN
 import os
 
+# for suffix in ["n", "s", "m", "l", "x"]:
 for suffix in ["n", "s", "m", "l", "x"]:
-    for soc in ["rk3562","rk3566", "rk3568", "rk3588"]:
-        INPUT_MODEL = 'yolov8{}.onnx'.format(suffix)
-        WIDTH = 320
-        HEIGHT = 320
-        OUTPUT_MODEL_BASENAME = 'yolov8{}'.format(suffix)
-        QUANTIZATION = False
-        DATASET = './dataset_coco10.txt'
+    # for soc in ["rk3562","rk3566", "rk3568", "rk3588"]:
+    for soc in ["rk3588"]:
+        # for QUANTIZATION in [True, False]:
+        for QUANTIZATION in [True]:
+            INPUT_MODEL = 'yolov8{}.onnx'.format(suffix)
+            WIDTH = 320
+            HEIGHT = 320
+            OUTPUT_MODEL_BASENAME = 'yolov8{}'.format(suffix)
+            # QUANTIZATION = False
+            DATASET = './datasets/coco20/dataset_coco20.txt'
 
-        # Config
-        MEAN_VALUES = [[0, 0, 0]]
-        STD_VALUES = [[255, 255, 255]]
-        QUANT_IMG_RGB2BGR = True
-        QUANTIZED_DTYPE = "asymmetric_quantized-8"
-        QUANTIZED_ALGORITHM = "normal"
-        QUANTIZED_METHOD = "channel"
-        FLOAT_DTYPE = "float16"
-        OPTIMIZATION_LEVEL = 2
-        TARGET_PLATFORM = soc
-        CUSTOM_STRING = None
-        REMOVE_WEIGHT = None
-        COMPRESS_WEIGHT = False
-        SINGLE_CORE_MODE = False
-        MODEL_PRUNNING = False
-        OP_TARGET = None
-        DYNAMIC_INPUT = None
+            # Config
+            MEAN_VALUES = [[0, 0, 0]]
+            STD_VALUES = [[255, 255, 255]]
+            QUANT_IMG_RGB2BGR = True
+            QUANTIZED_DTYPE = "asymmetric_quantized-8"
+            QUANTIZED_ALGORITHM = "normal"
+            QUANTIZED_METHOD = "channel"
+            FLOAT_DTYPE = "float16"
+            OPTIMIZATION_LEVEL = 2
+            TARGET_PLATFORM = soc
+            CUSTOM_STRING = None
+            REMOVE_WEIGHT = None
+            COMPRESS_WEIGHT = False
+            SINGLE_CORE_MODE = False
+            MODEL_PRUNNING = False
+            OP_TARGET = None
+            DYNAMIC_INPUT = None
 
-        OUTPUT_MODEL_FILE = "./output/{}/{}-{}x{}-{}.rknn".format(soc, OUTPUT_MODEL_BASENAME, WIDTH, HEIGHT, soc)
-        os.makedirs("./output/{}".format(soc), exist_ok=True)
+            if QUANTIZATION:
+                quant_suff = "-i8"
+            else:
+                quant_suff = ""
+            
+            OUTPUT_MODEL_FILE = "./output/{}/{}-{}x{}{}-{}.rknn".format(soc, OUTPUT_MODEL_BASENAME, WIDTH, HEIGHT, quant_suff, soc)
+            os.makedirs("./output/{}".format(soc), exist_ok=True)
 
-        rknn = RKNN()
-        rknn.config(mean_values=MEAN_VALUES,
-                    std_values=STD_VALUES,
-                    quant_img_RGB2BGR=QUANT_IMG_RGB2BGR,
-                    quantized_dtype=QUANTIZED_DTYPE,
-                    quantized_algorithm=QUANTIZED_ALGORITHM,
-                    quantized_method=QUANTIZED_METHOD,
-                    float_dtype=FLOAT_DTYPE,
-                    optimization_level=OPTIMIZATION_LEVEL,
-                    target_platform=TARGET_PLATFORM,
-                    custom_string=CUSTOM_STRING,
-                    remove_weight=REMOVE_WEIGHT,
-                    compress_weight=COMPRESS_WEIGHT,
-                    single_core_mode=SINGLE_CORE_MODE,
-                    model_pruning=MODEL_PRUNNING,
-                    op_target=OP_TARGET,
-                    dynamic_input=DYNAMIC_INPUT)
+            rknn = RKNN()
+            rknn.config(mean_values=MEAN_VALUES,
+                        std_values=STD_VALUES,
+                        quant_img_RGB2BGR=QUANT_IMG_RGB2BGR,
+                        quantized_dtype=QUANTIZED_DTYPE,
+                        quantized_algorithm=QUANTIZED_ALGORITHM,
+                        quantized_method=QUANTIZED_METHOD,
+                        float_dtype=FLOAT_DTYPE,
+                        optimization_level=OPTIMIZATION_LEVEL,
+                        target_platform=TARGET_PLATFORM,
+                        custom_string=CUSTOM_STRING,
+                        remove_weight=REMOVE_WEIGHT,
+                        compress_weight=COMPRESS_WEIGHT,
+                        single_core_mode=SINGLE_CORE_MODE,
+                        model_pruning=MODEL_PRUNNING,
+                        op_target=OP_TARGET,
+                        dynamic_input=DYNAMIC_INPUT)
 
-        # if rknn.load_pytorch("./input/" + INPUT_MODEL, [[HEIGHT, WIDTH, 3]]) != 0:
-        if rknn.load_onnx("./input/" + INPUT_MODEL) != 0:
-            print('Error loading model.')
-            exit()
+            # if rknn.load_pytorch("./input/" + INPUT_MODEL, [[HEIGHT, WIDTH, 3]]) != 0:
+            if rknn.load_onnx("./input/" + INPUT_MODEL) != 0:
+                print('Error loading model.')
+                exit()
 
-        if rknn.build(do_quantization=QUANTIZATION, dataset=DATASET) != 0:
-            print('Error building model.')
-            exit()
+            if rknn.build(do_quantization=QUANTIZATION, dataset=DATASET) != 0:
+                print('Error building model.')
+                exit()
 
-        if rknn.export_rknn(OUTPUT_MODEL_FILE) != 0:
-            print('Error exporting rknn model.')
-            exit()
+            if rknn.export_rknn(OUTPUT_MODEL_FILE) != 0:
+                print('Error exporting rknn model.')
+                exit()

dataset_coco10.txt

@@ -0,0 +1,10 @@
+./000000000285.jpg
+./000000000785.jpg
+./000000001296.jpg
+./000000001000.jpg
+./000000000776.jpg
+./000000000139.jpg
+./000000000632.jpg
+./000000000872.jpg
+./000000000724.jpg
+./000000001268.jpg