fig_img

app.py

@@ -1,7 +1,68 @@
+import spaces
+import sys
+print(sys.version_info)
+
 import gradio as gr
+#from florence import model_init, draw_image
+#from wikai import analyze_dial, ocr_and_od
+import matplotlib.pyplot as plt
+from aimodel import model_init, read_meter, visualization
+from test_rect import read_meter as read_meter_rect
+from PIL import Image
+from io import BytesIO
+import logging
+#logging.basicConfig(level=logging.DEBUG)
+print("Loading model...")
+@spaces.GPU
+def process_image(input_image:Image, meter_type:str):
+    fl, fl_ft = model_init(hack=False)
+    if meter_type == "方形儀表":    
+        value, img = read_meter_rect(input_image, fl, fl_ft)
+        return img, f"辨識結果: PA={value}", None
+    assert meter_type == "圓形儀表"    
+    plt.clf()
+    print("process_image")
+    W, H = 640, 480
+    if input_image is None:
+        return None, None    
+    meter_result  = read_meter(input_image, fl, fl_ft)
+    img, fig = visualization(meter_result)
+    buf = BytesIO()
+    fig.savefig(buf, format='png')
+    buf.seek(0)
+    fig_img = Image.open(buf)
+    plt.clf()
+    return img, f"辨識結果: PSI={meter_result.needle_psi:.1f}  kg/cm²={meter_result.needle_kg_cm2:.2f} ", fig_img
+
+with gr.Blocks() as demo:
+
+    gr.Markdown("## 指針辨識系統\n請選擇儀表類型，上傳圖片，或點擊Submit")
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                clear_button = gr.ClearButton()
+                submit_button = gr.Button("Submit", variant="primary")
+                meter_type_dropdown = gr.Dropdown(choices=["圓形儀表", "方形儀表"], label="選擇選項")
+            image_input = gr.Image(type="pil", label="上傳圖片")
+        with gr.Column():
+            number_output = gr.Textbox(label="辨識結果", placeholder="辨識結果")
+            image_output = gr.Image(label="輸出圖片")
+            plot_output = gr.Image(label="模型結果")
+
+    clear_button.add([image_input, image_output, number_output])
+
+    image_input.upload(
+        fn=process_image,
+        inputs=[image_input, meter_type_dropdown],
+        outputs=[image_output, number_output, plot_output],
+        queue=False
+    )
 
-def greet(name):
-    return "Hello " + name + "!!"
+    submit_button.click(
+        fn=process_image,
+        inputs=[image_input, meter_type_dropdown],
+        outputs=[image_output, number_output, plot_output],
+    )
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+demo.launch(debug=True)