gradio app added

.dvc/config

@@ -3,3 +3,5 @@
     remote = origin
 ['remote "origin"']
     url = https://dagshub.com/OperationSavta/SavtaDepth.dvc
+['remote "upstream"']
+    url = https://dagshub.com/OperationSavta/SavtaDepth.dvc

Procfile

@@ -0,0 +1 @@
+web: source setup.sh && python app_table.py

app_table.py

@@ -0,0 +1,36 @@
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+import gradio as gr
+
+
+def sales_projections(employee_data):
+    sales_data = employee_data.iloc[:, 1:4].astype("int").to_numpy()
+    regression_values = np.apply_along_axis(
+        lambda row: np.array(np.poly1d(np.polyfit([0, 1, 2], row, 2))), 0, sales_data
+    )
+    projected_months = np.repeat(
+        np.expand_dims(np.arange(3, 12), 0), len(sales_data), axis=0
+    )
+    projected_values = np.array(
+        [
+            month * month * regression[0] + month * regression[1] + regression[2]
+            for month, regression in zip(projected_months, regression_values)
+        ]
+    )
+    plt.plot(projected_values.T)
+    plt.legend(employee_data["Name"])
+    return employee_data, plt.gcf(), regression_values
+
+
+iface = gr.Interface(
+    sales_projections,
+    gr.inputs.Dataframe(
+        headers=["Name", "Jan Sales", "Feb Sales", "Mar Sales"],
+        default=[["Jon", 12, 14, 18], ["Alice", 14, 17, 2], ["Sana", 8, 9.5, 12]],
+    ),
+    ["dataframe", "plot", "numpy"],
+    description="Enter sales figures for employees to predict sales trajectory over year.",
+)
+iface.launch(auth=("admin", "pass1234"))

flagged/log.csv

@@ -0,0 +1,4 @@
+name,Output,timestamp
+Google,Hello Google!,2022-02-09 18:25:43.892129
+Google,Hello Google!,2022-02-09 18:25:45.867548
+Google,Hello Google!,2022-02-09 18:25:52.447643

requirements.txt

@@ -1,10 +1,13 @@
-dvc==1.11.15
-fastai==2.2.5
-torch==1.7.0
+#dvc==1.11.15
+#fastai==2.2.5
+#torch==1.7.0
 h5py==2.10.0
-opencv-python==4.4.0.42
-tqdm==4.52.0
-numpy==1.19.4
-scikit-learn==0.23.2
-dagshub==0.1.6
-tables==3.6.1
+#opencv-python==4.4.0.42
+#tqdm==4.52.0
+#numpy==1.19.4
+#scikit-learn==0.23.2
+#dagshub==0.1.6
+#tables==3.6.1
+fastapi
+gradio
+uvicorn

setup.sh

@@ -0,0 +1,2 @@
+export GRADIO_SERVER_NAME=0.0.0.0 
+export GRADIO_SERVER_PORT="$PORT"