### fix: lp01 processing

parent 16b9a6b3
 ... ... @@ -28,10 +28,9 @@ def tiller_prediction(LA, GDD_BBCH30): :return: Estimation of tiller count """ # LA is m^2/m^2 (= mm^2/mm^2) # scale to plot size of 125 * 50 * 3 (mm) LA = (LA / 1.0) * (0.125 * 0.15) # scale to mm^2 LA = LA * 10**(6) LA = LA * (125 * 50 * 3) #Asym: Model was fit to plot size of 125 * 50 * 3 (mm) Asym = 125 * 50 * 3 ... ... @@ -52,6 +51,7 @@ def tiller_prediction(LA, GDD_BBCH30): # x = (a/y - 1)^(-s) (e^m - (a/y - 1)^s) # Therefore: tiller_count = (Asym / LA - 1)**(-scal) * (math.exp(xmid) - (Asym / LA - 1) ** scal) tiller_count = tiller_count if tiller_count > 0 else 0 # Scale count to 1 m^2 tiller_count = (tiller_count / (0.125 * 0.15) ) * 1.0 ... ... @@ -132,10 +132,10 @@ def plant_prediction(image, delta_to_BBCH30, GSD): w_plant_count_total = np.sum(w_plant_counts) # Extract ground coverage > 50, normalize to 3 microplots (divide by sampling area, multiply by 3-microplot-area) a_area_gc50 = ( np.sum(image>255 * 0.5) ) / (image.shape * image.shape * (GSD*1000)**2) * (150 * 150) a_area_gc50 = ( np.sum(image>255 * 0.5) ) / (image.shape * image.shape * (GSD*1000)**2) * (150 * 125) # Calculate plant counts gc_plant_counts_total = a_area_gc50 * gc_slope + gc_intercept gc_plant_counts_total = gc_plant_counts_total / (150 * 150) * (image.shape * image.shape * (GSD*1000)**2) gc_plant_counts_total = gc_plant_counts_total / (150 * 125) * (image.shape * image.shape * (GSD*1000)**2) return(w_plant_count_total, gc_plant_counts_total) ... ... @@ -165,6 +165,9 @@ def process_plant_count(path_campaign, delta_to_BBCH30, design_label = parts plot_label = parts[:-4] elif (len(parts) == 3): if parts == "lp01": print(LA_image, " is lp01 overview image, skip") continue design_label = parts + "_" + parts plot_label = parts[:-4] elif (len(parts) == 4): ... ...
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